Balancing Renewable Electricity: Energy Storage, Demand Side Management, and Network Extension from an Interdisciplinary Perspective

Ethics of Science and Technology Assessment Volume 40 Book Series of the Europa¨ische Akademie zur Erforschung von Folgen wissenschaftlich-technischer Entwicklungen Bad Neuenahr-Ahrweiler GmbH edited by Carl Friedrich Gethmann

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Bert Droste-Franke Boris P. Paal Christian Rehtanz Dirk Uwe Sauer Jens-Peter Schneider Miranda Schreurs Thomas Ziesemer l

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Balancing Renewable Electricity Energy Storage, Demand Side Management, and Network Extension from an Interdisciplinary Perspective In collaboration with Ruth Klu¨ser and Theresa Noll

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Series Editor Professor Dr. Dr. h. c. Carl Friedrich Gethmann Europa¨ische Akademie GmbH Wilhelmstraße 56, 53474 Bad Neuenahr-Ahrweiler Germany On Behalf of the Authors Dr.-Ing. Bert Droste-Franke, Dipl.-Phys. Europa¨ische Akademie GmbH Wilhelmstraße 56, 53474 Bad Neuenahr-Ahrweiler Germany Desk Editor Friederike Wu¨tscher Europa¨ische Akademie GmbH Wilhelmstraße 56, 53474 Bad Neuenahr-Ahrweiler Germany Editing Franziska Mosthaf, Wortschleife Augsburg Germany

ISSN 1860-4803 e-ISSN 1860-4811 ISBN 978-3-642-25156-6 e-ISBN 978-3-642-25157-3 DOI 10.1007/978-3-642-25157-3 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2012930653 # Springer-Verlag Berlin Heidelberg 2012 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

The Europa¨ische Akademie The Europa¨ische Akademie zur Erforschung von Folgen wissenschaftlichtechnischer Entwicklungen GmbH is concerned with the scientific study of consequences of scientific and technological advance for the individual and social life and for the natural environment. The Europa¨ische Akademie intends to contribute to a rational way of society of dealing with the consequences of scientific and technological developments. This aim is mainly realised in the development of recommendations for options to act, from the point of view of long-term societal acceptance. The work of the Europa¨ische Akademie mostly takes place in temporary interdisciplinary project groups, whose members are recognised scientists from European universities. Overarching issues, e.g., from the fields of Technology Assessment or Ethic of Science, are dealt with by the staff of the Europa¨ische Akademie.

The Series The series Ethics of Science and Technology Assessment (Wissenschaftsethik und Technikfolgenbeurteilung) serves to publish the results of the work of the Europa¨ische Akademie. It is published by the academy’s director. Besides the final results of the project groups the series includes volumes on general questions of ethics of science and technology assessment as well as other monographic studies.

Acknowledgement The project “Energy Storages and Virtual Power Plants for the Integration of Renewable Energies into the Power Supply. Potentials, Innovation Barriers and Implementation Strategies” was supported by the German Aerospace Center (DLR). The content of the book is only the authors’ responsibility.

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Preface

Electricity supply is an important economic factor, particularly in industrialised societies. With restrictions in environmental effects, particularly with respect to greenhouse gas emissions, and in resources, technological innovations are called for which can contribute to producing electricity in a more environmentally friendly way than existing systems and at the same time providing sufficient supply security and economic efficiency. The question of challenges for innovation in the energy area was already generally discussed in Volume 18 of this book series which was also published in English translation as: “Sustainable Development and Innovation in the Energy Sector”, Springer Verlag. Based on the findings from the generic analysis in the above-mentioned study, but more focussed on specific technologies, Volume 32 concentrated on the interdisciplinary analysis of the regulation of electrical networks (“Die Regulierung elektrischer Netze. Offene Fragen und Lo¨sungsansa¨tze”), while Volume 36 worked on interdisciplinary perspectives of small fuel cell devices for house energy supply (“Brennstoffzellen und Virtuelle Kraftwerke. Energie-, umwelt- und technologiepolitische Aspekte einer effizienten Hausenergieversorgung”). The current study deals with an again more general problem with specific technological aspects: obtaining low-carbon strategies for balancing weather-caused fluctuations and potential gaps in supply prospectively occurring in systems with high shares of electricity production from renewable sources, particularly if wind and solar radiation are predominantly used. This purpose gains importance in view of the attempts in politics to reduce greenhouse gas emissions and, thus, such large shares of wind and solar power are envisaged for future energy systems in several countries, and particularly in the European Union. The study presents the results of the interdisciplinary work in the project “Energy Storages and Virtual Power Plants for the Integration of Renewable Energies into the Power Supply. Potentials, Innovation Barriers and Implementation Strategies”, which was carried out by the Europa¨ische Akademie GmbH and was funded by the German Aerospace Center (DLR). The necessary disciplinary broadness could be assured by using the instrument of ‘interdisciplinary project groups’ followed at the Europa¨ische Akademie. My personal thanks go to the members of the project group who coped with the task of the study, partly with strong personal engagement.

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Additionally, I would like to thank the German Aerospace Center (DLR) for the financial support of the project. The results should provide a scientific foundation for the political discussion about the integration of technologies using renewable energy sources for electricity production and hint at tangible innovation barriers. Furthermore, the study shows ways of adequately implementing strategies for low-carbon options that will be necessary with the high penetration of these technologies in future electricity systems. I hope that this book will get the attention in science, politics and the interested public it deserves. Bad Neuenahr-Ahrweiler August 2011

Carl Friedrich Gethmann

Foreword

Combating anthropogenic climate change is the major reason for the extensive restructuring of the electricity supply that is currently ongoing. The reduction of greenhouse gases by using renewable instead of fossil sources of energy is a widely accepted measure in this context. Respectively, the share of renewable energies is continuously increasing. In many countries, wind and solar radiation represent the major promising sources. Their availability strongly changes with weather conditions. In order to avoid that short-term fluctuations and long-term gaps in the electricity supply lead to shortages on the demand side, low-carbon technologies have to be developed which can take over the role of balancing supply and demand in such situations. In this context several questions arise: What are the major challenges for balancing energy and power in systems with a high share of electricity produced from renewable sources? Which promising low-carbon and long-term viable technology options for this purpose exist already or can prospectively be developed within the next years? Which obstacles for adequate innovation in that area can already be anticipated now and which strategies could be followed to remove or obviate these? In order to answer these questions, the Europa¨ische Akademie GmbH established the interdisciplinary project group “Energy Storages and Virtual Power Plants for the Integration of Renewable Energies into the Power Supply. Potentials, Innovation Barriers and Implementation Strategies” including experts from the relevant disciplinary areas of technical engineering, environmental science, economics, political science and jurisprudence. The project group started from individual disciplinary contributions, which were further discussed and integrated with regard to the overall task and composed to a consistent study. The major findings were finally condensed in policy recommendations. Most of the interdisciplinary discussions took place during the project group meetings, which were arranged about every 2 months. Two workshops and a conference were used to obtain additional input from experts outside the project group. The first workshop concentrated on discussing results from other studies in the area. The project group would like to thank the external experts for many valuable contributions during the first workshop: Frieder Borggrefe (Universita¨t zu Ko¨ln), Dr. Lueder von Bremen (Universita¨t Oldenburg),

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Dr. Clemens Hoffmann (Siemens AG), Dr. Cornelius Pieper (The Boston Consulting Group) and Detlef F. Sprinz, Ph.D. (Potsdam-Institut fu¨r Klimafolgenforschung). Furthermore, the group is grateful to Dr. Clemens Hoffmann and the Siemens AG for providing the opportunity to use their data for setting up a first version of a pan-European optimisation model considering power production from wind and solar radiation, storage options and grid connections in parallel to this project at RWTH Aachen, the idea for which was born during the first workshop. For the comprehensive review of interim results and valuable recommendations to further work on the subject, the group thanks the participants of the second workshop: Dr. Erik Hauptmeier (RWE AG, Essen), Dr. Wolfgang Woyke (E.ON AG, Mu¨nchen), Dr.-Ing. Michael Ritzau (Bu¨ro fu¨r Energiewirtschaft und technische Planung GmbH (BET), Aachen), Dr. Gerrit Volk (Bundesnetzagentur, Bonn), Ulla Bo¨de (Bundesnetzagentur, Bonn), Thomas Klaus (Umweltbundesamt, Dessau), Professor Uwe Leprich (Hochschule fu¨r Technik und Wirtschaft des Saarlandes, Saarbru¨cken) and Professor Joh.-Christian Pielow (Ruhr-Universita¨t Bochum). Special thanks go to the external contributors to the spring conference of the Europa¨ische Akademie in March 2010 for giving further insights into the studies and concepts with respect to the integration of renewable energies and in particular to the external speakers: Professor Kornelis Blok (Utrecht University), Andreas Brabeck (RWE AG, Essen), Vera Brenzel (E.ON, Du¨sseldorf), Jo¨rg-Werner Haug (citiworks AG, Mu¨nchen); Dr. Wolfram Krause (EWE AG, Oldenburg), Professor Hans Mu¨ller-Steinhagen (German Aerospace Center (DLR), Stuttgart/University of Stuttgart) and Dr.-Ing. Joachim Nitsch (German Aerospace Center (DLR), Stuttgart). Additionally the authors express their thanks to the group member Priv.-Doz. Dr. Dietmar Lindenberger (Universita¨t zu Ko¨ln) for his contributions in many good discussions during the meetings of the project group. Furthermore, thanks are due to Frieder Borggrefe and Dr. Matthias Leuthold for detailed discussions, especially for giving insights into aspects of energy system modelling. Many thanks go also to Dr. Stephan Lingner (Europa¨ische Akademie GmbH) for leading the first workshop and for making his valuable comments and contributions. Finally, the group thanks both Friederike Wu¨tscher (Europa¨ische Akademie GmbH) for the support in the publishing process and Wortschleife Augsburg for efficiently proofreading the text. Bad Neuenahr-Ahrweiler August 2011

Bert Droste-Franke

Contents

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Renewable Energies in the European Energy Mix . . . . . . . . . . . . . . . . . . . . . 1.3 Aim and Structure of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Future Perspectives of Electrical Energy Supply . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Aims for a Long-Term Viable Development of a Renewable-Based Electricity System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Efficient Allocation and Just Distribution . . . . . . . . . . . . . . . . . . . . . . 2.1.2 An Operative Action Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Indicators for the Evaluation of Balancing Strategies . . . . . . . . . . . . . . . . 2.2.1 Indicators for Environmental Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Indicators for Resource Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Indicators for the Design of the Energy Supply System . . . . . . . 2.3 Political Governance Towards a Renewable Energy Electricity System in Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Historical Background, Current Status and Development of Europe’s Energy System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1.1 Europe’s Growing Energy Dependence . . . . . . . . . . . . . . . . 2.3.1.2 Climate Change Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1.3 Climate Change as a Driving Force Behind the Search for a Low-Carbon Electricity System . . . . . . . . . . . . . . . . . . 2.3.1.4 Growing Diversification of the Energy Supply . . . . . . . . 2.3.1.5 Trends in Renewable Energy Production in Europe . . . 2.3.2 Political Governance Activities for Organising the Future Energy System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2.1 Regional Cooperation in Developing Renewables . . . . . 2.3.2.2 National Actions Within the EU on Climate Change and Renewable Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2.3 European Policies for a Low-Carbon Energy Market . . 2.3.2.4 The European Energy Council of 2011 . . . . . . . . . . . . . . . . 2.3.2.5 Moving Towards Higher Emission Reduction Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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2.3.2.6 Roadmap for a Low-Carbon Economy in 2050 . . . . . . . . 2.3.2.7 Supporting Infrastructure Development for Renewable Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2.8 Public Acceptance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Challenges Ahead . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Economics of Storing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Energy Economic Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Theory of Storing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2.1 Storing Values Without Technologies . . . . . . . . . . . . . . . . . . 2.4.2.2 Storing Values Using Technologies . . . . . . . . . . . . . . . . . . . . 2.5 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

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Existing Energy System Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Applicability of Existing Future Energy Scenarios as Framework Conditions for the Analysis of Strategies . . . . . . . . . . . . . 3.1.1 Energy System Modelling: A Theoretical Perspective . . . . . . . . . 3.1.2 Basic Approaches in Energy System Analysis Followed in This Study and Data Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3 Comparison of Relevant Energy System Analyses According to Their General Characteristics . . . . . . . . . . . . . . . . . . . . 3.2 The Derivation of Future Electricity Supply Parameters as Inputs for the Analysis of Balancing Strategies . . . . . . . . . . . . . . . . . . . . 3.2.1 Assumptions in the Political Renewable Energy Sources (RES) Scenario: Intensified Funding . . . . . . . . . . . . . . . . . . 3.2.2 Assumptions According to the Lead Scenario 2009 . . . . . . . . . . . 3.2.3 Effects on the Conventional Power Station Park . . . . . . . . . . . . . . . 3.2.3.1 Renewable Energy Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3.2 Fuel Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3.3 Resulting Power Station Parks . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.4 Evaluation of Development Paths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Demand for Balancing Electrical Energy and Power . . . . . . . . . . . . . . . . . . 4.1 Assessing the Balancing Demand and Storage Employment Based on Scenarios for Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 Assessing the Demand of Balancing Electrical Energy and Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1.1 Effect on the Residual Load and the Available Power Station Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1.2 Characteristics of Possible Wind Calms Lasting Several Days . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1.3 Dimensioning the Necessary Storage Capacity . . . . . . . . 4.1.2 Estimation of the Storage Employment . . . . . . . . . . . . . . . . . . . . . . . .

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4.2 Assessing the Storage Demand Based on an Optimised Pan-European Low-Carbon Electrical Energy Supply Strategy . . . . . . 4.2.1 General Aspects and Boundary Conditions . . . . . . . . . . . . . . . . . . . . 4.2.2 Power Flow Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 System Optimisation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.4 Cost Data and Other Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.5 First Model Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.6 Discussion of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

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Technologies for Balancing Electrical Energy and Power . . . . . . . . . . . . . 83 5.1 Classification of Energy Storage Systems and Systems Offering Positive and Negative Control Power . . . . . . . . . . . . . . . . . . . . . . . 83 5.2 Technical Description of “Electricity to Electricity” Energy Storage Technologies for a Balanced Electrical Energy and Power Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 5.2.1 “Mechanical” Storage Systems for Electric Power . . . . . . . . . . . . 86 5.2.1.1 Compressed Air Energy Storage (CAES) . . . . . . . . . . . . . . 86 5.2.1.2 Pumped Hydropower Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 5.2.1.3 Hydro Storage Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.2.1.4 Flywheels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.2.2 “Electrical” Storage Systems for Electric Power . . . . . . . . . . . . . . 92 5.2.2.1 Electrochemical Double-Layer Capacitors (“Supercaps”) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 5.2.2.2 Superconducting Coils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.2.3 “Chemical” Storage Systems for Electric Power . . . . . . . . . . . . . . . 93 5.2.3.1 Lead-Acid Batteries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.2.3.2 High Temperature Sodium-Based Batteries . . . . . . . . . . . . 94 5.2.3.3 Lithium-Ion Batteries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 5.2.3.4 Nickel Cadmium (NiCd) and Nickel-Metal-Hydride (NiMH) Batteries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 5.2.3.5 Redox-Flow Batteries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 5.2.3.6 Hydrogen Storage Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.3 Technical Description and Potential of “Electricity to Anything” Energy Storage Technologies for a Balanced Electrical Energy and Power Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.3.1 DSM Industrial Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.3.2 Balance Provision by Electrical Mobility . . . . . . . . . . . . . . . . . . . . . 100 5.3.3 DSM Household Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 5.3.3.1 Technical Potential of DSM in the Household Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 5.3.3.2 Expected Economic Benefits from DSM in the Household Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 5.3.4 Shutdown of Renewable Power Generation . . . . . . . . . . . . . . . . . . . 108 5.3.5 Generation of Chemical Fuels such as Hydrogen, Methane or Methanol from Electricity . . . . . . . . . . . . . . . . . . . . . . . . 108

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5.4 Technical Description of “Anything to Electricity” Energy Storage Technologies for a Balanced Electrical Energy and Power Supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.1 CHP Plants with Thermal Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Conventional Power Plants Using Fossil, Nuclear, Hydro or Biofuels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Conclusions on Options for Demand Response and Demand-Side Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Life Cycle Cost Analysis of Storage Technologies . . . . . . . . . . . . . . . . . . 5.7 Assessment of Future Viability of the Technologies’ Environmental Issues, Resource Use and System Characteristics . . . 5.7.1 Methodology and Data Applied for Quantitative Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.2 Environmental Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.2.1 Assessment Methodology and Assumptions . . . . . . . . . 5.7.2.2 Environmental External Costs of Balancing Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.2.3 Environmental Impacts of Balancing Technologies Differentiated into Categories . . . . . . . . . . . . . . . . . . . . . . . . 5.7.3 Resource Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.3.1 Types and Amounts of Resources Required . . . . . . . . . 5.7.3.2 Current Availability of Relevant Mineral Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.3.3 Resource Potentials for the Production of Balancing Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.4 System Characteristics Relevant for Society . . . . . . . . . . . . . . . . . . 5.7.4.1 Supply Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.4.2 Risk Avoidance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.4.3 Openness to Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7.5 Conclusions on the Future Viability of Various Approaches to Energy Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.8 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Technology of Electricity Networks and Economical Impacts . . . . . . . 6.1 Assessment of Technical Barriers Considering the Total System Including Network Requirements . . . . . . . . . . . . . . . . . . . . . 6.1.1 Interaction of Load Control with the Distribution Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.2 Transmission Network Expansion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Economical Impacts of Balancing Activities at the Daily and Seasonal Scales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.1 Distribution Network Requirements for Avoiding Restrictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Effects of the Transmission Network Expansion Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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6.2.3 Conclusions on Economical Impacts of Balancing Activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 6.3 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 7

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Economic Analysis and Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Problems in a Market Economy without Economic Policy: Weather-Based Supply and Culturally Caused Demand Fluctuations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.1 The Insurance Function of the Market . . . . . . . . . . . . . . . . . . . . . . . . 7.1.2 Fluctuations and Smoothing of Electricity Demand: Energy Saving Reduces the Demand for Storage Facilities . . . . . . . . . . . 7.1.3 Fluctuations and Smoothing of Supply . . . . . . . . . . . . . . . . . . . . . . . . 7.1.4 Coordination of Supply and Demand . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.5 Aspects of Long-Run Developments . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.6 Towards a Theory of Location for Storage Facilities . . . . . . . . . 7.2 Analysis of Economic Framework Conditions . . . . . . . . . . . . . . . . . . . . . . . 7.2.1 Introduction: The Theory of Economic Policy . . . . . . . . . . . . . . . . 7.2.2 The Theory of Economic Policy in the Area of Environmental and Technology Problems . . . . . . . . . . . . . . . . . 7.2.2.1 Tradable CO2 Permits, Taxes and Other Instruments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2.2 Research and Technical Progress: Trusting Markets Only Versus Support for Complementary Technologies? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2.3 Beyond Pigovian Corrections . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2.4 Policies for Imported Resources and Political Risks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.3 The Current Practice of Government Support . . . . . . . . . . . . . . . . . 7.2.4 Stylised Views on Economic Policy: First Best, Second Best, History and Transition . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.4.1 First Best . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.4.2 Second Best . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.4.3 Historical Heritage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.4.4 Transition to Science Based Views . . . . . . . . . . . . . . . . . . . 7.2.5 Economic Policy Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Legal Analysis of Balancing Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Introductory Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Energy Storage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1 Centralised Storage Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1.1 Planning and Licensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1.2 Regulatory Incentives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1.3 Access . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1.4 Unbundling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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163 163 164 166 166 167 168 169 169 170 170

171 172 172 172 173 173 174 175 175 176 177 179 179 180 180 180 181 181 184

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8.2.2 Decentralised Storage Systems, Especially E-mobility . . . . . . . 8.2.2.1 Legal Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.2.2 Contractual Relationships Within Networks . . . . . . . . . 8.2.2.3 Questions Concerning Data Protection . . . . . . . . . . . . . . . 8.3 Balancing Strategies in Distribution Grids . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.1 Smart Meter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.1.1 Topics Regarding Data Protection . . . . . . . . . . . . . . . . . . . . 8.3.1.2 Contractual Relationships in Networks . . . . . . . . . . . . . . . 8.3.2 Smart Grid/Demand-Side Management . . . . . . . . . . . . . . . . . . . . . . . 8.3.2.1 Data Protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.2.2 Contractual Relationships in Networks . . . . . . . . . . . . . . . 8.4 Transmission Network Expansion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.1 The Status Quo for Planning and Licensing of Network Expansion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2 The Status Quo of Investment Regulation as Part of Economic Energy Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2.1 Unbundling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.2.2 Network Investment Duties for TSOs . . . . . . . . . . . . . . . . 8.4.2.3 Investment Planning Duties of TSOs as an Instrument of Reflexive Steering . . . . . . . . . . . . . . . . . . . . . 8.4.2.4 Investment Incentives and Securing Investments as an Aspect of Price Regulation . . . . . . . . . . . . . . . . . . . . . . . . 8.4.3 Concepts for a Reform of Planning, Licensing and Regulating of Network Expansion . . . . . . . . . . . . . . . . . . . . . . . . 8.4.3.1 National Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.3.2 European Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.4 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Conclusions and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Overall Aim and Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Challenges and Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2.1 Development of Technical Infrastructure . . . . . . . . . . . . . . . . . . . . . 9.2.2 Framework Conditions and Organisational Aspects . . . . . . . . . . 9.2.2.1 Market Conditions for Balancing Technologies . . . . . . 9.2.2.2 Specific Support for the Application of Balancing Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

185 185 187 189 190 190 191 195 195 196 196 196 197 200 201 201 203 205 207 207 209 211 213 213 214 215 217 217 220

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 List of Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Further volumes of the series Ethics of Science and Technology Assessment (Wissenschaftsethik und Technikfolgenbeurteilung) . . . . . . . . . . . . . . . . . . . 251

Abbreviations

2040+ AA-CAES ACER AEUV ARegV BEWAG BDEW BDSG BGB BMU

BMWi BNetzA BRIC Br BVerfGE CAES CC CCS CH4 CHP CL CO2 CSP ct/kWh

Possible situation in 2040, 2050 or later Adiabatic-Compressed Air Energy Storage European Agency for the Cooperation of the Energy Regulators Vertrag u¨ber die Arbeitsweise der Europa¨ischen Union (see also TFEU) Anreizregulierungsverordnung (Incentive Regulation Ordinance) Berliner Sta¨dtische Elektrizita¨tswerke Aktien-Gesellschaft Bundesverband der Energie- und Wasserwirtschaft (Federal Association of Energy and Water Industry) Bundesdatenschutzgesetz (Federal Data Privacy Law) Bu¨rgerliches Gesetzbuch (Civil Law Code) Bundesministerium fu¨r Umwelt, Naturschutz und Reaktorsicherheit (Federal Ministry for the Environment, Nature Conservation and Nuclear Safety) Bundesministerium fu¨r Wirtschaft und Technologie (Federal Ministry of Economics and Technology) Bundesnetzagentur (Federal Network Agency) Group of the four (big emerging) nations Brazil, Russia, India and China Bromium Bundesverfassungsgericht (Federal Constitutional Court) Compressed Air Energy Storage Combined Cycle Carbon Capture and Storage Methane Combined Heat and Power Controllable Loads Carbon Dioxide Concentrated Solar Power Cent per kilowatt hour

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xviii

DECP DENA DIN DLR DOD DR DSM E-DeMa

E2P EC EDLC EEC EEFA EEG EMEP EnLAG ENTSO-E EnWG EU EU-15 EU-27 EUCO Eurostat ETG ETS EWI Fe FPC GasNZV GDP

Abbreviations

Decentralised Energy Conversion Plants Deutsche Energie-Agentur GmbH (German Energy Agency) Deutsches Institut fu¨r Normung e.V. (German Institute for Standardisation) Deutsches Zentrum fu¨r Luft- und Raumfahrt e.V. (German Aerospace Center) Depth of Discharge Demand Response Demand Side Management Project on “Development and demonstration of locally networked energy systems to the E-Energy marketplace of the future” Energy to power ratio – installed capacity in kWh divided by the peak power in kW European Commission Electrochemical Double-Layer Capacitors European Energy Council Energy Environment Forecast Analysis (EEFA GmbH & Co. KG) Gesetz fu¨r den Vorrang Erneuerbarer Energien (Erneuerbare EnergienGesetz) (Renewable Energy Law) European Monitoring Evaluation Programme Gesetz zum Ausbau von Energieleitungen (Power Lines Expansion Law) European Network of Transmission System Operators for Energy Gesetz u¨ber die Elektrizita¨ts- und Gasversorgung (Energiewirtschaftsgesetz) (German Energy Act) European Union European Union (member states before eastward enlargement) European Union (all current members) European Council Statistical Office of the European Union Energietechnische Gesellschaft im VDE (Society for Energy Technics) Emission Trading Scheme Energiewirtschaftliches Institut an der Universita¨t zu Ko¨ln (Energy Economic Institute at the University of Cologne) Iron Final Power Consumption Verordnung u¨ber den Zugang zu Gasversorgungsnetzen (Gas Network Access Ordinance) Gross Domestic Product

Abbreviations

GIC GIL GKSS

GPP GS GT GW GWh GWB GWP GWS HCB HU HV HVDC IAEA ICCG ICE ICT IEA IER

IfnE IGCC IPCC ISO ITO kV kVA kW kWh kWh/a KWKG

LCC LNG LNS LV

xix

Gas-Insulated Conductors Gas-Insulated Lines Helmholtz-Zentrum Geesthacht Zentrum fu¨r Material- und Ku¨stenforschung GmbH (Centre for Materials and Coastal Research) Gross Power Production Gas and Steam Power Station Gas Turbine Power Station Gigawatt Gigawatt hour Gesetz gegen Wettbewerbsbeschra¨nkung (Act Against Restraints of Competition) Global warming potential (assessed for a specific time horizon) Gesellschaft fu¨r wirtschaftliche Strukturforschung (Institute of Economic Structures Research) House Connection Boxes Housing Units High-Voltage High-Voltage Direct Current International Atomic Energy Agency International Centre for Climate Governance Internal Combustion Engine Information and Communication Technology International Energy Agency Institut fu¨r Energiewirtschaft und Rationelle Energieanwendung (Institute for Energy Economics and the Rational Use of Energy), Universita¨t Stuttgart Ingenieurbu¨ro fu¨r neue Energien Integrated Gasification Combined Cycle Intergovernmental Panel on Climate Change Independent System Operator Independent Transmission Operator Kilovolt Kilovolt-Ampere Kilowatt Kilowatt hour Kilowatt hour per year Gesetz fu¨r die Erhaltung, die Modernisierung und den Ausbau der Kraft-Wa¨rme-Kopplung (Kraft-Wa¨rmeKopplungsgesetz) Life Cycle Costs Liquefied Natural Gas Local Network Station Low-Voltage

xx

MV MVA MW MWh NaBr NaBr3 NaNiCl2 Battery NaS Battery Na2S2 Na2S4 NAV

NCC NEEDS NH3 NiCd Battery NiMH Battery NMVOC NOx ODP OECD PDA PHEV PIA PLC ppb PSS pu PV R&D RD&D RE RES ROV r.p.m. SO2 SRU SVC

Abbreviations

Medium-Voltage Megavolt-Ampere Megawatt Megawatt hour Sodium Bromide Sodium Tribromide Sodium-Nickel-Chloride Battery, also ZEBRA battery Sodium-Sulphur Battery Disodium Disulphide Sodium Tetrasulfide Verordnung u¨ber Allgemeine Bedingungen fu¨r den Netzanschluss und dessen Nutzung fu¨r die Elektrizita¨tsversorgung in Niederspannung (Netzanschlussverordnung) (Ordinance for Regulating Grid Connection) Network Connection Capacity New Energy Externalities Development for Sustainability (integrated project) Ammonia Nickel-Cadmium Battery Nickel-Metal-Hybride Battery Non-Methane Volatile Organic Compounds Nitrogen Oxides (reactive oxides of nitrogen, nitrogen dioxide (NO2) and nitrogen monoxide (NO)) Ozone Layer Depletion Organisation for Economic Co-operation and Development Personal Digital Assistant Plug-in Hybrid Electric Vehicles Privacy Impact Assessment Power Supply Infrastructure Parts per billion Pump Storage Station Per unit system Photovoltaics Research and Development Research, Development and Demonstration Renewable Energies Renewable Energy Sources Raumordungsverordnung (Regional Planning Procedure) Revolutions Per Minute Sulphur Dioxide Sachversta¨ndigenrat fu¨r Umweltfragen (German Advisory Council for Environmental Issues) Static Var Compensator

Abbreviations

TEN TEN-E TFEU TREC TSO TWh UCTE UK UPS USA USGS VDE V2+, V3+, V4+, V5+ VRLA Wh Wh/kg WTO YOLL ZEBRA

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Transeuropean Networks Transeuropean Energy Networks Treaty on the Function of the European Union Trans-Mediterreanean Renewable Energy Corporation Transmission System Operator Terawatt hour Union for the Co-Ordination of Transmission of Electricity United Kingdom Uninterruptible Power Supply United States of America United States Geological Survey Verband der Elektrotechnik Elektronik Informationstechnik (Association for Electrical, Electronic & Information Technologies) Vanadium in various oxidation states Valve-Regulated Lead-Acid Watt hour Watt hour per kilogram World Trade Organisation Years of Life Lost s. NaNiCl2 Battery

.

Summary

Background and Aim of the Study An important aim behind the restructuring of Germany’s and Europe’s electricity systems is to reduce their environmental burden, especially with respect to greenhouse gas emissions. Emissions must be brought down to a level that is sustainable in the long-run and consistent with greenhouse gas emission reduction goals. Meeting these goals will require a system that will be able to cope simultaneously with the fundamental demands for economic efficiency, environmental sustainability and supply security. Making use of existing scenarios, this study sketches such a system. It focuses in particular on auxiliary systems for electricity production, such as energy storage methods and network extensions. The study introduces technologies that can balance electricity in energy systems and that can serve as enabling technologies for the integration of large quantities of renewable energies in the power supply system. It begins with a discussion of normative aims for the future electricity system before continuing with a description of current policies and political developments and an overview of relevant existing energy system studies. These sections serve as background for the remainder of the study. They are followed by discussion and analysis of the growing demand for means to balance the fluctuations found in electricity generated in power systems with a high penetration of renewable energies, the potentials of diverse technologies, requirements for electrical networks, economic impacts and important legal issues. Finally, the main challenges to the achievement of developing balancing technologies and processes for renewable electricity-dominant systems are summarised and recommendations made. With respect to the legal regulations, the status quo as of April 2011 is assumed in the study.

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Summary

Aims for the Future and the Status Quo of Electricity Systems in Europe The basic normative aims underlying this study of a future renewable electricitydominated system are tied to the general economical principals of efficient allocation and just distribution. These principals are critical to characterising and evaluating policies and options that could become part of a future electricity system. Diverse economic discussions point to several trade-offs that exist among technical efficiency, low prices and environmental constraints. However, they also reveal that these trade-offs can be resolved by use of an action rule that is formulated on four priorities (see Sect. 2.1 of the main text): 1. protection of the environment and, thus, society from unacceptable effects; 2. preservation of the total value of produced and natural capital; 3. maximisation of the intertemporal welfare of current and future generations under the restrictions of the first and second priorities; and 4. just distribution of basics for meeting needs at present. The action rule can be filled with content by applying indicators that evaluate technologies, policies and developments with respect to their environmental and societal aspects. The classification that was chosen for the evaluation of energy systems subdivides between protection of the environment, resource use and availability, and system characteristics with respect to society (see Sect. 2.2 of the main text). An analysis of the political processes in the last about 20 years shows the development and potential shortcomings of energy politics (see Sect. 2.3 of the main text). Experts are worried about the potential unacceptable damage to the environment and society that could be caused by climate change. This has led to the establishment of limits on emissions of greenhouse gases. These limits have been defined politically by the international community. Experts’ concerns are also the basis for the politically set quotas for energy produced from renewable technologies. Renewable energy’s share of electricity production in Europe has shown large growth rates in recent years. This growth is expected to continue into the future. Still, there are many governance challenges ahead. For example, it will be necessary to encourage the international energy market, particularly in European countries, to strengthen technical infrastructure, and especially, electricity grids. It will also be important to assess to what extent Europe’s rising competence in energy questions should be further extended. In addition, it will be necessary to find ways to address opposition to large-scale projects that may be acceptable from certain long-term environmental and societal normative perspectives, but may still encounter opposition among parts of society that object for various reasons to their development. This holds also for large-scale projects tied to technical systems that will be required for an expansion of renewable energy use. Adequate procedures for assuring stakeholder participation in decision-making processes will be essential. Theoretical investigations about storing electricity as a means of storing economic value (s. Sect. 2.4 of the main text) identify three options that can be followed to

Summary

xxv

balance the demand for and supply of electricity in a system with a high amount of power produced from wind and solar radiation. First is to expand grid connections, particularly for transboundary transmissions, and to adjust the installation of wind and solar power to enable good potentials for the exchange of electricity in times of regional shortages. Second is to over-install conventional power plant capacity, for example, with natural gas-fired facilities, in order to be able to compensate a lack in supply. Third is to build options for energy storage and to introduce measures that can influence demand for electricity.

Existing Energy System Analyses Continents are the appropriate scale for analyses of the technical and economical potentials for electricity systems that can balance electricity demand and supply at the regional level. Yet, in Europe, energy policy is still to a large extent seen as a matter of national sovereignty and competence. This means that for this interdisciplinary analysis, national energy scenarios and targets are primarily used. The case of Germany is taken as an example of a large nation in Europe with a strong economy and ambitious targets for the development of renewable energies. A review of studies (see Sect. 3.1 of the main text) showed that two main methodological approaches are followed by policy-oriented analyses of electricity systems in Germany. For those analysing the time period of the next 10–20 years, temporal exploratory scenarios building on economic optimisation mechanisms tend to be made. For scenarios that cover the present up to about 2050, a target system is typically defined and pathways for realising it are then analysed. Comparing the main scenarios calculated for Germany reveals the importance of being clear about the assumptions being used, using consistent parameters and carrying out further sensitivity analyses. This is crucial for purposes of interpretation and development of policy support based on the findings of the basically complementary studies. The approach chosen for the system analyses in this study is: First, to investigate how a long-term viable energy system could be realised. This is to be done by analysing potential future scenarios where there is a high share of renewable energies in the system and low-carbon balancing strategies are employed. And second, to identify factors which can or should be adapted to realise adequate framework conditions for the innovation processes needed for achieving a longterm viable energy system. It was beyond the scope of this study to develop completely new scenarios that include an energy conversion system. Instead, with the goal of concentrating attention on balancing technologies in systems with a high share of renewables, two existing scenarios have been selected as a starting point for analysis (see Sect. 3.2 of the main text): the “lead scenario 2009” that follows a roadmapping approach (Nitsch and Wenzel 2009) and an explorative political scenario with ambitious environmental aims (scenario “III” from Lindenberger et al. 2008). Scenarios of the requirements for balancing electricity supply and demand are

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Summary

investigated for 2030 and “2040+”.1 The analysis produced for 2040+ based on the outcome of the “lead scenario” shows that additional measures such as storage, peak load control or securing renewable energy imports will be required to realise a functioning power system.

Demand for Balancing Electrical Energy and Power when there is a High Penetration of Renewable Energies in the System Looking in more detail into the technical characteristics of the two selected scenarios for representative days (“type days”) in Germany with respect to the residual load (see Sect. 4.1.1.1 of the main text), i.e., the load that could not be covered by the remaining controllable power generators in the system, reveals for the lead scenario a maximum temporal power deficiency in 2030 of 7 GW and in 2040+ of 18 GW. For 2030, the maximum temporal power surplus results are 13.7 GW and for 2040, 24 GW. Four TWh of electricity in 2030 (1.4% of annual total feed-in of renewables) and 21 TWh in 2040+ (4.7% of annual total feed-in of renewables) cannot be used in the system. These numbers show that there is a potential for using storage technologies. The dimension that storage options should take is mainly determined by the additional power and energy required during wind calms (see Sects. 4.1.1.2 and 4.1.1.3 of the main text). Analysing wind calms of several strengths and lengths shows that if these are to be covered only by storing electricity, storage power has to cover in total 18 GW in 2030 and 35 GW in 2040+. The energy capacity of the storage options in order to cope with the maximum energy demand has to amount in total to 600 GWh in 2030 and 1,700 GWh in 2040+. The dimension of the storage facilities is, in the 2030 scenario, determined by wind calms in which 5% of the installed power is not exceeded (in other words, at least 95% reduction) during 87 h, and in 2040+ by long wind calms (218 h) with at least 80% power reduction. The requirements could be lowered to the extent secured electricity can be imported. Assuming exemplary compressed air energy storages (CAES) and neglecting peak reductions in the calculation of generation costs, net-benefits from applying energy storage facilities can be calculated (see Sect. 4.1.2 of the main text). The calculations show that reductions in generation costs, in the case of 15 GW additional storage power, exceed for the case of 2040+ the annuities of the investment, which means that using CAES with the assumed characteristics would be economical, even if the opportunity of getting peak prices is not considered. Additional to this analysis of scenarios for Germany, a pan-European modelling approach was developed and realised during the study (see Sect. 4.2 of the main text). It optimises the system of power production from wind and solar radiation, electricity network and energy storages on the basis of hourly meteorological data for 7 years and technical and cost estimates for a future period around 2040 and

1

2040+ represents a situation in a year around 2040 or later.

Summary

xxvii

beyond. Historical “burden”, in the form of already existing power plants, was neglected in order to analyse an optimised system without restrictions other than weather conditions, specific costs and available technologies. First model runs have been performed. The model mechanism relies on a genetic algorithm, optimising “individuals” specified by the various characteristics of the electricity system, expressed in cost values.

Technologies for Balancing Electrical Energy and Power Looking at attributes of different technologies for balancing electrical energy and power reveals that the performance of a technology strongly depends on the specific situation for which it should be applied. Accordingly, technology options including storage technologies, as well as demand-side management and conventional power plants, can be categorised based on the following characteristics (see Sects. 5.1, 5.2, 5.3, 5.4, and 5.5 of the main text): A) type and location of the systems, B) duration and frequency of supply, C) type of input and output energy. Simulating the application for different typical cases allows the derivation of cost estimates, which can be projected to future years (see Sect. 5.6 of the main text). According to the results of this analysis, the following can be said for the different analysed tasks. The assumed technical requirements are listed in brackets: – Long-term storage (power2: 500 MW, available energy: 100 GWh, 1.5 cycles per month): For this task, costs of 10 €ct/kWh seem to be achievable using the option of storing electrical energy in the form of hydrogen, which is much lower than the estimated achievable costs for compressed air energy storage (CAES) (about 23 €ct/kWh). The potentials in Germany are high. In contrast, the option of pumped hydro is, with achievable costs of less than 5 €ct/kWh, much cheaper, but offers only small potential in Germany, and transferring electricity from outside Germany, e.g., from Scandinavia will prospectively require the expansion of transmission lines. In case an extra line has to be built for the storage option and the line is only used for this purpose, the total costs may reach the same level as those that could be achieved by hydrogen storage. – Load levelling in the transportation grid (power: 1 GW, available energy: 8 GWh, 1 cycle per day): For this task pumped hydro plants are also interesting with the same cost values as for long-term storage. Additionally, compressed air storage technologies, especially the adiabatic variant with achievable costs also below 5 €ct/kWh, could become interesting alternatives. Furthermore, batteries can well be used

2

Charging/discharging power are set equal for the definition of tasks.

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for load levelling, although they are more expensive than the other two options. They show the advantage of being able to deliver also primary reserve. – Peak shaving in the distribution grids (power: 100 kW, available energy: 250 kWh, 2 cycles per day): In this area, several battery systems, including zinc-bromine, vanadium redoxflow, lithium-ion, nickel-cadmium, lead-acid and sodium-sulphur or sodiumchloride are competing. The best guess, from today’s point of view, would estimate the achievable costs for sodium systems to be the lowest, followed by the lead-acid technology, which is the cheapest variant at present. Additionally to the options that could be economical due to low specific costs, potentials from the double use of storage technologies, such as batteries for electric vehicles and small photovoltaic systems in houses, could also be relevant in the future. The total potential of demand-side management, including electric vehicles, combined heat and power plants, control of industrial load, heat pumps and white goods, is estimated to be around 16–23 GW theoretically and about 10 GW taking consumer acceptance into account. Beyond the installation of storage options, the shutting-down of wind and solar power plants during extreme high supply peak events will still be necessary from technical, economical and legal points of view. As for the future viability of storage systems, life cycle screenings of relevant technologies show that the expected large reductions of CO2 in the energy system will lead to a higher importance of emissions generated in the production of materials (see Sect. 5.7.2 of the main text). Due to high emissions of SO2 in some important processes, ecosystem effects may gain interest. With a much lower use of fossil energy resources projected for the future, the use and availability of mineral resources, particularly for the production and application of new energy technologies, including balancing technologies, will become increasingly important. An analysis of the availability of these mineral resources in terms of their reserve-to-production ratio, high regional concentration of reserves, and prices and price changes (see Sect. 5.7.3 of the main text), shows that of the analysed substances only titanium is unproblematic. There are also only a few problems with availability for lithium, vanadium, arsenic, nickel and zircon oxide. Concerning mineral resources used in batteries, large-scale use of lithium type, lead-acid and vanadium batteries will require high recycling rates and potentially the development of substitutes in the long run. Analysing a set of indicators gathered from relevant publications for system characteristics of balancing technologies with small modular systems provide a positive picture (see Sect. 5.7.4 of the main text). In contrast, large central systems may be linked to problems of import dependency, may require large efforts to reach sufficient redundancy, and face acceptance issues in the local population. This suggests the importance of participatory decision-making processes. Additionally, adequate measures have to be implemented to keep the risk of accidents with sudden uncontrolled release of the stored energy low. In order not to hamper the development of options for balancing supply and demand of electricity at a high

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share of renewable energy use, implemented funding schemes have to be designed to be technologically neutral.

Electricity Network Aspects Expanding the use of renewable resources for electricity production and using the balancing options discussed above also requires an extension of electricity grids. This concerns both the transmission and the distribution grid, nationally and internationally. An investigation of technical restrictions in distribution grids (see Sects. 6.1.1 and 6.2.1 of the main text) shows that with the enabling of demand-side management, the capacities of distribution grids will soon be reached due to an increase in simultaneity of load. Breaching the operation boundaries can be avoided by coordinating load and generation in the distribution grid. In order to maximise demand-side management also with respect to maximal acceptance, automated procedures should be developed. The total costs of network reinforcements necessary with a penetration of decentralised controllable loads, which can be expected from 2020 onwards, are estimated to be about 1,000 € per household. These are high compared to the estimated annual generation cost savings of about 18 € per household. Based on calculations for the transmission grid with typical days (“type days”) (see Sects. 6.1.2 and 6.2.2 of the main text), an extension of about 3,000 km or more is needed in the long run to cope with the regional shifting of feed-in towards substantial offshore expansion. However, this installation would be able to cope only with about 70% of the maximum installed wind capacity. In rare extreme situations in which wind power exceeds 70% of the maximal power, electricity generation will have to be curtailed to prevent damage to the grid infrastructure. Furthermore, extreme exchange of electricity with neighbouring countries is not accounted for in the assessment of required grid extension in this study. Other studies allowing extreme offshore feed-in and exchange result in a required expansion of about 3,500 km already in 2020. Considering the current status and the anticipated advance of technology development, the most plausible technologies applied will be a combination of conventional overhead lines with high-voltage direct current (HVDC) lines. The investments in the long term (2040+) can thus be estimated, through calculations on the basis of type days, amounting to 6–8 billion €, or about 0.2–0.35 €ct/kWh of feed-in from wind power plants.

Economic Policy Options for the Use of Storage Systems The theoretical analysis of potential problems in a market economy due to weatherdependent electricity supply and culturally caused demand fluctuations (see Sect. 7.1 of the main text) shows that several benefits can be gained from applying

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balancing options in the electricity system. An improvement of the cross-border infrastructure can help dampen the fluctuations caused by deliveries from regions with high supply/demand ratios to those with low supply/demand ratios. Suppliers as well as traders could be interested in operating storage systems. While suppliers will prospectively locate the systems close to the source, traders will tend to locate them close to customers. Grid operators ideally could locate storage facilities close to points in the network with high instability. However, the European Union’s unbundling directive currently does not allow grid operators to operate energy storage systems to any significant extent. The benefits for markets and society to be derived from energy storage facilities can justify policy intervention (see Sect. 7.2 of the main text). With the use of storage systems, the stability of supply will be enhanced, environmental externalities – particularly those caused by climate change – will be reduced, monopoly power in times of scarce supply could be reduced by strengthening decentralised renewable energy systems, and the reliance on technologies with uninsurable uncertainty (nuclear power) can be reduced, or in the case of Germany, eliminated. For historical reasons, however, other technologies are being supported by governmental funding. Considering practical realities, funding beyond the currently provided support for research, development and demonstration projects is important.

Legal Analysis of Framework Conditions There are several major legal issues with respect to installing strategies for balancing demand and supply of electricity which are brought to light by this study’s legal analysis. The issues can be subdivided into: central storage systems (see Sect. 8.2 of the main text) and decentralised storage systems, including the options of demand-side management and smart grids (see Sect. 8.3 of the main text), and the expansion of transmission networks (see Sect. 8.4 of the main text). With respect to central storage systems, in the cases of both current and pending laws, it is necessary to clarify whether the application of storage technologies applies to the supply layer or the grid layer. The legal classification influences how civil law applies to such issues as non-discriminating use and access as well as unbundling. Several disincentives and barriers to making investments into storage technologies can be identified in existing legislation. The actors most affected are the producers of electricity from renewable energies and the transmission system operators who are obliged by the German Renewable Energy Law (ErneuerbareEnergien-Gesetz (EEG)) to buy and market “renewable power”. Additionally, a special planning regime for utilising underground resources could help to mitigate potential conflicts among the users themselves and between them and the respective landowners. In order to not hamper the development of energy storage technologies through legal regulation, disincentives should be abolished. For decentralised storage systems, particularly e-mobility, smart grid and demandside management, contractual issues related to the completely new actors and networks that will emerge will have to be defined. Such issues as duties of care,

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cooperation and information provision, as well as conditions of use will need to be addressed. The possibility that such technological systems could lead to the creation of far-reaching and extremely detailed individual mobility and energy use profiles requires consideration of the extent to which current legislation can deal with data protection concerns. This is especially the case considering the quantity and quality of data that will be collected as well as the new kinds of assessments, processing and use of that data which may occur. New solutions that could lie within or outside the existing legal framework for data protection will have to be assessed. Current regulations covering procedures for the expansion of transmission grids are very diverse but also, in certain areas, dysfunctional. Most problematic appear to be the punctual investment duties of network operators tackled in civil court procedures, not adequately considering macroeconomic aspects (e.g., } 9 EEG). A more comprehensive and systematic approach is needed. For the national level, a fundamental reform model for strategic transmission investment projects could improve the situation. Some refinements and standardisation including, for instance, good practice guidelines for public hearing procedures may improve the handling of conflicts with the affected local population. The potentials for reforms on the EU level are limited. However, a better coordination on this level would be useful.

Challenges and Recommendations The requirements for balancing electrical energy in the system will increase with the rising share of electricity produced from renewable energies. As the above summary of the analysis made in this study indicates, several challenges are tied to the introduction of low CO2 emission options, including energy storage systems, demand-side management, the over-installation of capacity in electricity production, and grid expansion, that could provide the stable electricity performance needed in different locations in Europe. Done correctly, these systems could provide stable performance at all relevant time scales from seconds to days to weeks. To conclude, the 13 challenges that were identified in this study (see Sect. 9.2 of the main text) are listed together with summaries of the respective recommendations that were drawn up for addressing them. Challenge 1: Providing Sufficient Storage Capacity for Germany – A mix of storage options should be installed, which is coordinated with respect to network restrictions, in order to limit the shutting down of facilities in high supply peak situations and provide low-carbon options for filling gaps. – International networks should be established to further develop and use large storage potentials in some European countries. – Over-installation in capacity of wind and solar power plants together with sufficient transporting capacity should be considered as options.

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– Alternative technical options should be further analysed, e.g., using gas networks for storing energy. – Disincentives from legal regulation should be removed and avoided in the future. – RD&D of technologies should be intensified in order to reduce costs of storage technologies.

Challenge 2: Realising Technical Potentials of Decentralised Options – Automated technical solutions to control loads should be developed in order to prevent reductions of user comfort. – Flexible tariffs should be introduced to increase the acknowledgement of scarcities and temporally changing values of electric energy. – Data requirements should be minimised in the required control procedures and adequate data protection regimes should be installed. – RD&D for standardisation should be further pushed with respect to automated load management.

Challenge 3: Managing Environment and Resource Use – Appropriate design of technologies should include early assessments of potential hindrances to a technology’s large-scale application due to limited supply of required resources or environmental effects. – Continuous monitoring of specific resource use and markets should be carried out during development. – RD&D of mineral recycling and substitutes should be established and respective procedures implemented where necessary.

Challenge 4: Providing Sufficient Network Capacity for Electricity Transport – Acceleration of planning procedures should be established by means of more structured mechanisms. – Strengthening of national and European interests in relation to regional interests in network extension should be reached through reforming the respective regulation systems. – R&D should be fostered by the regulator through accepting the respective costs for refunding.

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Challenge 5: Adequate Implementation of Balancing Technologies in Regulations – Attributions and definitions with respect to balancing technologies should be clarified in the relevant regulations. – Decisions on attributing storage facilities to the grid or power generation level should be made by the legislator.

Challenge 6: Designing a European Energy Market – Exchange of electricity should be enabled by further strengthening the transmission grid. – A low-carbon energy framework should be implemented for Europe, which is comprehensive, long-term oriented and far-reaching/challenging and goes beyond 2020. – Europe’s electricity generation markets should be further integrated.

Challenge 7: Removing the Historical Heritage of Subsidies and Taxes – Ideal economic framework conditions should be established by taking back outdated subsidies and taxes and installing consistent measures such as demonstration projects and temporally limited startup subsidies instead on a stepwise basis. – Historically determined drawbacks in framework conditions should be countered by temporary subsidies and tax arrangements.

Challenge 8: Transforming Market Externalities to Costs and Earnings – Socio-economic benefits should be internalised through establishing respective markets and compensation mechanisms. – Costs of system services should be internalised by installing mechanisms for power generators paying for provided system services, including grids that they require for proper facility operation. – Advantages of coordination between production of electricity from renewable energies, grid management and usage of storage technologies for benefits realisation should be analysed. – Potential business cases should be analysed in detail. – Detailed system analysis of benefits from applying balancing technologies should be performed as a basis for policy decisions.

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Challenge 9: Handling New Complex Market Structures – Contractual challenges in the new markets should be analysed in detail. – General legal measures for new markets should be developed.

Challenge 10: Strengthening Scientific Advice on Balancing Options – Energy system analysis should be extended by means of intensive research with full-scale models, including the coordinated cooperation of relevant institutions with complementing models. – Large-scale projects on energy system modelling should be established and the advantages of institutionalisation, allowing regular updating and monitoring of system developments, should be analysed. – The European perspective, considering different national politics, should be mandatory for extended energy system analyses. – The required installed power and energy capacity should be analysed in detail as one major focus of future studies.

Challenge 11: Adequately Supporting the Application of New Technologies – Startup subsidies based on market mechanisms should be implemented, and phased out automatically to the level of externality compensation in order to adequately promote the application of promising technologies. – Investments in RD&D for storage systems should be increased.

Challenge 12: Adequately Supporting Long-Term Investments – Political decisions on boundary conditions on a national and international level should be reliably fixed for the long term, in line with basic principles of European competition policy. – A sound basis for decisions on boundary conditions should be generated by extended energy system analysis.

Challenge 13: Handling Opposition to Large-Scale Projects – Adequate mechanisms for the participation of affected parties and the wider public in decision making should be implemented. – Installing a special planning regime for underground resources should be analysed with respect to its potential for mitigating possible conflicts among the relevant interest groups. – Measures for conflict resolution, such as the provision of adequate compensation measures should be further analysed and – where appropriate – applied.

Zusammenfassung

Hintergrund und Zielsetzung Ein wesentliches Ziel der Umstrukturierung des Elektrizita¨tssystems in Deutschland und Europa ist die Reduzierung der erzeugten Umweltbelastung, vor allem durch Treibhausgase, auf ein langfristig zukunftsfa¨higes Maß. Es wurden Minderungsziele fu¨r Emissionsmengen festgelegt, deren Einhaltung langfristig zu einer akzeptablen Belastung von Umwelt und Gesellschaft fu¨hren soll. Eine wichtige Grundlage fu¨r die Einhaltung dieser Ziele ist die schrittweise Entwicklung eines Elektrizita¨tssystems, das zuku¨nftig den Anforderungen von o¨konomischer Effizienz, Umweltfreundlichkeit und Versorgungssicherheit gerecht werden kann. Die vorliegende Studie skizziert ein solches System basierend auf verfu¨gbaren Szenarien. Der Schwerpunkt liegt dabei auf technischen Systemen zur Unterstu¨tzung der eigentlichen Elektrizita¨tserzeugung wie Energiespeichern und Netzausbau. In der Studie werden Technologien diskutiert, mit denen die Nachfrage und das Angebot an Elektrizita¨t ausgeglichen werden, womit die Nutzung großer Mengen Elektrizita¨t aus erneuerbaren Energien ermo¨glicht werden kann. Zuna¨chst werden normative Ziele fu¨r das zuku¨nftige Elektrizita¨tssystem vorgestellt und die derzeitige Entwicklung in Politik, Gesellschaft und Technologien beschrieben; ¨ berblick u¨ber bestehende relevante Energiesystemstudien. Diese es folgt ein U Arbeiten dienen als Grundlage fu¨r weitere Analysen, anhand derer der Bedarf an Ausgleichskapazita¨t in Systemen mit hohem Anteil erneuerbarer Energien in der Elektrizita¨tserzeugung abgescha¨tzt wird, Potentiale verschiedener Technologien diskutiert werden, Anforderungen an elektrische Netze ermittelt werden, Kosten und Politikoptionen untersucht werden, wichtige regulatorische Aspekte behandelt werden und, abschließend, Empfehlungen zu den identifizierten Herausforderungen formuliert werden. Maßgeblich fu¨r die Untersuchungen ist der Stand der gesetzlichen Regelungen im April 2011.

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Ziele fu¨r eine zukunftsfa¨hige Entwicklung und der Status Quo von Elektrizita¨tssystemen in Europa Zur Ableitung grundlegender normativer Ziele fu¨r ein zukunftsfa¨higes Elektrizita¨tssystem werden in der Studie die fundamentalen wirtschaftlichen Prinzipien der effizienten Allokation und der gerechten Verteilung herangezogen. Diese werden operationalisiert, um politisches Handeln und Optionen fu¨r ein zuku¨nftiges Elektrizita¨tssystem einordnen und bewerten zu ko¨nnen. Aus o¨konomischer Sicht bestehen verschiedene Zielkonflikte zwischen technischer Effizienz, niedrigen Preisen und umweltseitigen Belastungsgrenzen. Diese ko¨nnen aufgelo¨st werden, indem man eine Handlungsregel in vier absteigenden Priorita¨ten formuliert (s. Abschnitt 2.1 im Haupttext): 1. Schutz der Umwelt und damit der Gesellschaft vor inakzeptablen Auswirkungen; 2. Erhaltung des Gesamtwerts des ada¨quat bewerteten produzierten und natu¨rlichen Kapitals; 3. Maximierung der gesamten Wohlfahrt derzeitiger und zuku¨nftiger Generationen unter Einhaltung der ersten zwei Priorita¨ten; 4. gerechte Verteilung von Grundlagen in der Gegenwart. Durch die Heranziehung entsprechender Indikatoren kann die Handlungsregel fu¨r die Bewertung von Technologien, politischen Handelns und politischer Entwicklungen verwendet werden. In der Studie werden dazu die drei Bereiche Schutz der Umwelt, Ressourcennutzung/-verfu¨gbarkeit und Systemcharakteristiken im Hinblick auf die Gesellschaft unterschieden (s. Abschnitt 2.2 im Haupttext). Eine Analyse der politischen Prozesse der vergangenen etwa zwanzig Jahre in dieser Studie (s. Abschnitt 2.3 im Haupttext) zeigt Entwicklungen und Versa¨umnisse in der Energiepolitik auf. Einige Ergebnisse werden im Folgenden zusammenfassend dargestellt. Experten befu¨rchten, dass durch den beobachteten Klimawandel inakzeptable Auswirkungen auf Umwelt und Gesellschaft entstehen ko¨nnten. Deshalb wurden von der internationalen Gemeinschaft Grenzen fu¨r die Emission von “Treibhausgasen” politisch definiert und gesetzlich festgelegt. Diese dienten auch als Basis fu¨r die Festlegung von Quoten auf den Anteil erneuerbarer Energien im Energiesystem. Bereits heute ist in Europa ein starker Anstieg in der Verwendung erneuerbarer Energien fu¨r die Stromproduktion zu verzeichnen, der sich vermutlich weiter fortsetzen wird. Allerdings bestehen nach wie vor große Herausforderungen fu¨r die Politik, z.B. die Sta¨rkung des internationalen Elektrizita¨tsmarktes. Dafu¨r sollten vor allem weitere europa¨ische La¨nder in den Markt einbezogen werden, wozu ein Ausbau der technischen Infrastruktur, in erster Linie die Erweiterung der elektrischen Netze, erforderlich wird. Zusa¨tzlich sollte untersucht werden, inwiefern die gegenwa¨rtig wachsende Zusta¨ndigkeit Europas in der Regelung von Energiefragen weiter versta¨rkt werden sollte. Die Erfahrung zeigt außerdem, dass einige Großprojekte, die aus langfristig umweltseitiger und gesellschaftlich normativer Sicht akzeptiert oder sogar gewu¨nscht werden, in Teilen der Bevo¨lkerung auch auf Ablehnung stoßen. Das gilt unter anderem auch

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fu¨r Technologien, die fu¨r eine weitere Ausweitung der Nutzung erneuerbarer Energien notwendig sind. Deswegen werden ada¨quate Prozeduren fu¨r die Beteiligung von Interessensvertretern an Entscheidungsprozessen erforderlich sein. Theoretische Untersuchungen der Speicherung von Elektrizita¨t als Mittel zur Speicherung o¨konomischer Werte (s. Abschnitt 2.4 im Haupttext) zeigen auf, dass drei Optionen in einem System mit einem hohen Anteil von Elektrizita¨t aus Wind- und Solarkraft verfolgt werden ko¨nnen, um Nachfrage und Angebot von Elektrizita¨t auszugleichen. Die erste sieht vor, die internationalen Netzverbindungen, ¨ bertragungsnetz, auszubauen und die Installation von Windkraftanlagen vor allem das U und solar betriebenen Anlagen so anzupassen, dass ein großes Potential fu¨r den Stromaustausch bei regional unterschiedlichem Elektrizita¨tsbedarf entsteht. Die zweite Option besteht darin, konventionelle Kraftwerke u¨ber die ohnehin beno¨tigte Kapazita¨t hinaus zusa¨tzlich allein fu¨r den Ausgleich vorzuhalten. Die dritte beinhaltet den Aufbau von Energiespeicheroptionen inklusive Nachfragesteuerung.

Bestehende Energiesystemanalysen Hinsichtlich der technischen und o¨konomischen Potentiale fu¨r den regionalen Ausgleich von Elektrizita¨tsnachfrage und -angebot wird deutlich, dass Kontinente die richtigen geographischen Skalen fu¨r Energiesystemanalysen sind. Jedoch liegt die Energiepolitik in Europa nach wie vor vorwiegend in den Ha¨nden der jeweiligen souvera¨nen Staaten. Daher werden in dieser Studie in erster Linie nationale Energieszenarien fu¨r die interdisziplina¨re Analyse herangezogen. Deutschland wird als ein Fallbeispiel fu¨r eine große europa¨ische Nation mit einer ¨ konomie und gleichzeitig ambitionierten Zielen bezu¨glich der Nutzung starken O erneuerbarer Energien analysiert. Eine Bestandsaufnahme (s. Abschnitt 3.1 im Haupttext) zeigt, dass in den vorhandenen Analysen des deutschen Elektrizita¨tssystems, die zur Politikberatung herangezogen werden, im Wesentlichen zwei Ansa¨tze verfolgt werden: Wa¨hrend die Entwicklungen in den na¨chsten zehn bis zwanzig Jahren, also bis 2020 bzw. 2030, hauptsa¨chlich durch zeitlich explorative Szenarien, die auf o¨konomischer Optimierung basieren, untersucht werden, werden langfristige Analysen mit Blick auf 2050 durchgefu¨hrt, indem zuna¨chst Zielsysteme definiert und dann mo¨gliche Pfade zu ihrer Realisierung analysiert werden. Ein Vergleich der einschla¨gigen Studien zeigt die Wichtigkeit weiterer Offenlegungen der Annahmen, der Verwendung konsistenter Parameter und der Durchfu¨hrung weiterer Sensitivita¨tsanalysen fu¨r die Interpretation der Ergebnisse mit dem Ziel der Politikberatung und fu¨r die Kombination der Aussagen aus den sich prinzipiell erga¨nzenden Studien. Fu¨r die Systemanalysen in dieser Studie wird folgender Ansatz verfolgt: zuerst wird eine Analyse der Zielsituation, in der ein langfristig zukunftsfa¨higes System zur Elektrizita¨tsversorgung erreicht ist, durchgefu¨hrt. Dazu werden potentielle zuku¨nftige Elektrizita¨tssysteme auf ihren Bedarf und die Potentiale von Technologien fu¨r den Ausgleich von Angebot und Nachfrage elektrischer Energie hin untersucht. In einem zweiten Schritt werden dann Maßnahmen identifiziert, die bereits heute

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erfolgen ko¨nnten, um ada¨quate Rahmenbedingungen fu¨r die erforderlichen Innovationsprozesse zu gewa¨hrleisten. Da in der vorliegenden Studie keine Gesamtkonzepte zuku¨nftiger Elektrizita¨tssysteme inklusive der Erzeugung neu zu entwickeln waren und sie sich vielmehr auf die Betrachtung erga¨nzender Technologien zum Ausgleich von elektrischer Energie bei einem hohen Anteil erneuerbarer Energien konzentrieren soll, wurden zwei bereits vorhandene Studien als Grundlage fu¨r die Analysen herangezogen (s. Abschnitt 3.2 im Haupttext): Das “Leitszenario 2009” als Pfadanalyse (genauer: “roadmapping”-Ansatz, Nitsch and Wenzel 2009) und ein exploratives politisches Szenario mit ambitionierten Umweltzielen (Szenario “III” von Lindenberger et al. 2008). Auf ihrer Basis wurden fu¨r die zwei zuku¨nftigen Jahre 2030 und “2040+”3 Anforderungen an den Ausgleich des Angebots und der Nachfrage elektrischer Energie untersucht. Als erstes Ergebnis aus der Analyse der Anlagenparks ergibt sich, dass im Falle des Leitszenarios im Zieljahr 2040+ zusa¨tzliche Maßnahmen wie der Bau von Speichersystemen, Lastmanagement oder Absicherung der Importe von Strom aus erneuerbaren Energien notwendig sind, um ein funktionierendes System zu realisieren.

Bedarf an Ausgleich elektrischer Energie und Leistung bei einem hohen Anteil erneuerbarer Energien im System Eine genaue Analyse der technischen Charakteristika der zwei ausgewa¨hlten Szenarien fu¨r Deutschland im Hinblick auf die residuale Last, d.h. der Last, die zeitweise nicht durch die Kraftwerke im System abgedeckt werden kann, auf Basis repra¨sentativer Tage (“Typtage”) (s. Abschnitt 4.1.1.1 im Haupttext) ergab fu¨r das Leitszenario ein maximales Leistungsdefizit zur Deckung von Lu¨cken im Stromangebot in 2030 von 7 GW und in 2040+ von 18 GW. Der maximale ¨ berschuss an elektrischer Leistung ergab sich in 2030 zu 13,7 und zeitweise U in 2040+ zu 24 GW. Dabei kann elektrische Energie in Ho¨he von 4 TWh (2030, 1,4 Prozent der ja¨hrlichen Einspeisung aus erneuerbaren Energien) bzw. 21 TWh (2040+, 4,7 Prozent der ja¨hrlichen Einspeisung aus erneuerbaren Energien) nicht im System genutzt werden. Diese Zahlen zeigen bereits, dass ein gewisses Potential fu¨r die Nutzung von Speichertechnologien besteht. Die Auslegung der Speicheroptionen ist hauptsa¨chlich bestimmt durch die Menge zusa¨tzlicher Leistung und Energie, die fu¨r den Ausgleich von Windstillen beno¨tigt wird (s. Abschnitte 4.1.1.2 und 4.1.1.3 im Haupttext). Die Analyse von Windstillen verschiedener Sta¨rken und La¨ngen zeigt, dass eine reine Abdeckung des zusa¨tzlichen Leistungsbedarfs durch Speicher in der Summe eine Speicherleistung von 18 GW in 2030 und 35 GW in 2040+ erfordern wu¨rde. Die Energiekapazita¨t der Speicheroptionen mu¨sste insgesamt 600 GWh in 2030 und 1.700 GWh in 2040+ betragen, um die jeweils maximal beno¨tigte Energiemenge abdecken zu ko¨nnen.

3

2040+ entspricht einer Situation in einem Jahr um 2040 oder spa¨ter.

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In den Betrachtungen fu¨r 2030 wird die zur Abdeckung von Produktionseinbru¨chen notwendige Dimension des Gesamtspeichers durch eine Windstille bestimmt, in der 5 Prozent der installierten Leistung u¨ber 87 Stunden nicht u¨berschritten werden (d.h.: bei der 87 Stunden lang eine Reduktion um mindestens 95 Prozent zu beobachten ist). In 2040+ ergibt sich die Dimensionierung der Speicher durch eine Windstille mit 218 Stunden La¨nge und mindestens 80 Prozent Reduktion der Leistung. Die Anforderungen ko¨nnen in dem Maße verringert werden in dem gesicherte Elektrizita¨t importiert werden kann. Unter der beispielhaften Annahme der Nutzung von Druckluftspeichern (“Compressed Air Energy Storages” (CAES)) und der Vernachla¨ssigung der Reduktion von Spitzen bei der Berechnung der Erzeugungskosten wurde der finanzielle Gewinn durch die Speichernutzung ermittelt (s. Abschnitt 4.1.2 im Haupttext). Die Berechnungen ergeben, dass im Fall von 15 GW zusa¨tzlich installierter Speicherleistung in 2040+ die Reduktionen in den Erzeugungskosten die Annuita¨ten des Investments u¨bersteigen. Das bedeutet, dass Druckluftspeicher mit den angenommenen Charakteristiken selbst ohne die Beru¨cksichtigung von Preisen, die in Spitzenlastzeiten erzielt werden ko¨nnen, o¨konomisch betrieben werden ko¨nnten. Zusa¨tzlich zu dieser Analyse von bestehenden Szenarien fu¨r Deutschland wurde im Projekt ein pan-europa¨ischer Modellansatz entwickelt und parallel dazu numerisch umgesetzt (s. Abschnitt 4.2 im Haupttext). Mit ihm wird das System bestehend aus Elektrizita¨tserzeugung aus Wind und Sonneneinstrahlung, Elektrizita¨tsnetzen und Energiespeichern auf der Basis stu¨ndlicher meteorologischer Daten fu¨r sieben Jahre unter technischer sowie kostenseitiger Annahmen fu¨r ein zuku¨nftiges Jahr um 2040 und spa¨ter (2040+) optimiert. Vorgaben durch historisch gewachsene Energiesysteme, wie die Zahl und Art bereits bestehende Kraftwerke, werden dabei vernachla¨ssigt, womit fu¨r die Optimierung zuna¨chst keine Restriktionen außer Wetterbedingungen, spezifischen Kosten und verfu¨gbaren Technologien bestehen. Der Modellmechanismus fußt auf einem genetischen Algorithmus, der iterativ “Individuen” optimiert, die sich durch verschiedene Charakteristiken des Energiesystems auszeichnen und in Form von Kostenwerten ausgedru¨ckt werden. Mit dem Modell wurden erste Berechnungen durchgefu¨hrt.

Technologien fu¨r den Ausgleich elektrischer Energie und Leistung Die Betrachtung der Eigenschaften verschiedener Technologien, die prizipiell fu¨r den Ausgleich elektrischer Energie und Leistung herangezogen werden ko¨nnen, zeigt, dass ihre Verwendbarkeit stark von der jeweiligen Aufgabe abha¨ngt. Technische Optionen wie Speichertechnologien aber auch Lastmanagement und konventionelle Kraftwerke ko¨nnen daher gut kategorisiert werden, indem ihre Charakteristiken im Hinblick auf die folgenden Bereiche angegeben werden (s. Abschnitte 5.1 bis 5.5 im Haupttext): A) Typ und Einsatzort des Speichersystems, B) Dauer und Ha¨ufigkeit des Speicherangebots, C) Form der gespeicherten und der bereitgestellten Energie.

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Zusammenfassung

Die Simulation der Realisierung fu¨r typische Fa¨lle erlaubt es, potentielle zuku¨nftige Kosten abzuscha¨tzen (s. Abschnitt 5.6 im Haupttext). Auf Basis der Analyse ergeben sich folgende Aussagen fu¨r die untersuchten drei verschiedenen Aufgaben. Die Annahmen fu¨r die technischen Anforderungen sind jeweils in Klammern dargestellt: – Langzeitspeicherung (Leistung4: 500 MW, verfu¨gbare Energie: 100 GWh, 1,5 Zyklen pro Monat): Fu¨r diese Aufgabe scheinen Kosten von 10 €-Cent/kWh erreichbar zu sein, wenn Elektrizita¨t in Form von Wasserstoff gespeichert wird. Dieser Wert ist deutlich geringer als die abgescha¨tzten Kosten fu¨r Druckluftspeicher (CAES) (ca. 23 €-Cent/kWh). Die Potentiale in Deutschland sind hoch. Im Gegensatz dazu sind die Kosten fu¨r Pumpspeicherkraftwerke mit 5 €-Cent/kWh zwar geringer, aber die Potentiale in Deutschland sind sehr beschra¨nkt. Bei Nutzung von Potentialen außerhalb Deutschlands, z.B. in Skandinavien, muss außerdem beru¨cksichtigt werden, dass dazu ein entsprechender Ausbau des ¨ bertragungsnetzes notwendig ist. Sollte sogar eigens fu¨r die Nutzung des U Speichers eine Netzverbindung gebaut werden mu¨ssen und sollte diese nur fu¨r diesen Speicher genutzt werden, ko¨nnen die Gesamtkosten dieselbe Ho¨he erreichen wie die fu¨r die Speicherung in Wasserstoff. – Lastausgleich im U¨bertragungsnetz (Leistung: 1 GW, verfu¨gbare Energie: 8 GWh, 1 Zyklus pro Tag): Fu¨r diese Aufgabe sind ebenfalls Pumpwasserkraftwerke interessant. Sie ko¨nnen voraussichtlich zu denselben niedrigen Kosten wie im Fall der Langzeitspeicherung betrieben werden. Zusa¨tzlich ka¨me der Einsatz von Druckluftspeichern, besonders der adiabatisch arbeitenden Varianten, mit erreichbaren Kosten unter 5 €-Cent/kWh in Frage. Des Weiteren ko¨nnen Batterien gut fu¨r den Lastausgleich genutzt werden, obwohl sie voraussichtlich ho¨here Kosten als die anderen zwei Optionen aufweisen werden. Dafu¨r haben sie den Vorteil, auch Prima¨rreserve bereitstellen zu ko¨nnen. – Bereitstellung von Spitzenlast (peak shaving) in den Verteilnetzen (Leistung: 100 kW, verfu¨gbare Energie: 250 kWh, 2 Zyklen pro Tag): In diesem Bereich konkurrieren verschiedene Batterietechnologien miteinander, insbesondere Zinc-Brom-, Vanadium-Redox-Flow-, Lithium-Ionen-, NickelCadmium-, Blei-Sa¨ure- und Natrium-Schwefel- oder Natrium-Nickel-ChloridTechnologien. Aus heutiger Sicht werden die erreichbaren spezifischen Kosten fu¨r Natrium-Systeme am niedrigsten eingescha¨tzt, gefolgt von der Blei-Sa¨ureTechnologie, welche heute die kostengu¨nstigste Variante darstellt. Zusa¨tzlich zu den kostengu¨nstigen Optionen werden voraussichtlich auch Potentiale durch Doppelnutzung von Speichern wie Batterien in Elektrofahr-

4

Fu¨r die Definition der Aufgaben sind Ladungs- und Entladungsleistung als gleich angenommen worden.

Hintergrund und Zielsetzung

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zeugen und stationa¨re Batterien in Geba¨uden, die z.B. zur Erga¨nzung kleiner Photovoltaikanlagen eingesetzt werden, in Zukunft relevant werden. Das gesamte Potential von Lastmanagement inklusive der Steuerung von Elektrofahrzeugen, Kraftwa¨rmekopplungsanlagen, Industrielasten, Wa¨rmepumpen und weißer Ware (Ku¨hlschra¨nke, Waschmaschinen, etc.) wird theoretisch auf etwa 16 bis 23 GW abgescha¨tzt. Unter Beru¨cksichtigung der begrenzten Akzeptanz beim Konsumenten reduziert es sich auf etwa 10 GW. Neben der Installation von Speicheroptionen wird es aus technischer, o¨konomischer und rechtlicher Sicht zusa¨tzlich notwendig sein, Wind- und Solaranlagen bei extremen Angebotsspitzen abzuschalten. Abscha¨tzungen der Zukunftsfa¨higkeit von Speichersystemen auf Basis von Daten zu Lebenszyklusanalysen zeigen, dass die erwarteten starken Reduktionen in der Menge der CO2-Emissionen im Energiesystem voraussichtlich dazu fu¨hren werden, dass die bei Produktionsprozessen von Materialien wie Nickel und Blei entstehenden Emissionen relevanter werden (s. Abschnitt 5.7.2 im Haupttext). Aufgrund hoher SO2-Emissionen in einigen wichtigen Prozessen ko¨nnten u.a. ¨ kosysteme an Bedeutung gewinnen. entsprechende Auswirkungen auf O Durch die zuku¨nftig geringere Ausbeutung fossiler Energieressourcen ru¨ckt die Nutzung und Verfu¨gbarkeit von mineralischen Ressourcen sta¨rker in den Fokus. Dies gilt insbesondere fu¨r die Produktion und den Betrieb neuer Energietechnologien, unter anderem solcher, die zum Ausgleich von elektrischer Energie und Leistung verwendet werden ko¨nnen. Die Analyse der Verfu¨gbarkeit mineralischer Ressourcen unter Beru¨cksichtigung der statischen Reichweite, regionaler Konzentrationen von Reserven, Preise und Preisa¨nderungen (s. Abschnitt 5.7.3 im Haupttext) zeigt, dass von den analysierten Rohstoffen lediglich Titan unproblematisch ist, wa¨hrend einzelne wenige Probleme mit Lithium, Vanadium, Arsen, Nickel und Zirkonoxid absehbar sind. Nimmt man den heutigen Ressourcenbedarf fu¨r die Herstellung und den Betrieb von Batterien auch fu¨r zuku¨nftige Technologien an, wird die Verwendung der untersuchten Batterietechnologien Lithium-Typ-, Blei-Sa¨ure- und Vanadium-Akkumulatoren in großen Mengen langfristig hohe Recyclingraten und mo¨glicherweise die Substitution derzeit beno¨tigter Mineralien erfordern. Die Analyse der Systemcharakteristik der betrachteten Ausgleichstechnologien anhand typischer, hier verwendeter Indikatoren fu¨r diesen Bereich kommt vor allem fu¨r kleine modulare Systeme zu einem positiven Ergebnis (s. Abschnitt 5.7.4 im Haupttext). Bei großen zentralen Systemen kann es zu ho¨herer Importabha¨ngigkeit kommen; es muss ein gro¨ßerer Aufwand betrieben werden, um ausreichend Redundanz im System vorzuhalten, und die begrenzte Akzeptanz der lokalen Bevo¨lkerung ist zu beru¨cksichtigen, wodurch voraussichtlich die Nutzung partizipativer Elemente in den Entscheidungsverfahren wichtig sein wird. Zusa¨tzlich mu¨ssen ada¨quate Maßnahmen ergriffen werden, um das Risiko von Unfa¨llen unter plo¨tzlicher Abgabe gespeicherter Energie gering zu halten. Um zu vermeiden, dass die Entwicklung von Ausgleichsoptionen fu¨r Angebot

xlii

Zusammenfassung

und Nachfrage von elektrischer Energie behindert wird, mu¨ssen die implementierten Fo¨rdersysteme technologieneutral gestaltet werden.

Implikationen fu¨r Elektrizita¨tsnetze Die Ausweitung der Nutzung erneuerbarer Ressourcen fu¨r die Elektrizita¨tsproduktion und die Anwendung der oben diskutierten Ausgleichsoptionen erfordern zusa¨tzlich ¨ bertragungsnetz als einen Ausbau der Elektrizita¨tsnetze. Das betrifft sowohl das U auch die Verteilnetze, sowohl national als auch international. Eine Untersuchung technischer Restriktionen in Verteilnetzen (s. Abschnitt 6.1.1 und 6.2.1 im Haupttext) zeigt auf, dass die Kapazita¨ten bei Nutzung von Laststeuerung (“demand side management”) wegen der ansteigenden Gleichzeitigkeit der Lasten voraussichtlich schnell erscho¨pft sein werden. Die Verletzung operativer Grenzen kann dadurch verhindert werden, dass Last und Erzeugung im Verteilnetz koordiniert werden. Um die Umsetzung der Laststeuerung im Hinblick auf ihren Nutzungskomfort zu optimieren, sollte sie so weit wie mo¨glich automatisiert werden. Fu¨r die notwendige Versta¨rkung der Verteilnetze werden Kosten von 1.000 € pro Haushalt abgescha¨tzt, die bei Ausnutzung des Potentials Laststeuerung voraussichtlich ab 2020 zu investieren sind. Diese sind im Vergleich zu den ja¨hrlich eingesparten Erzeugungskosten von ungefa¨hr 18 € pro Haushalt hoch. ¨ bertragungsnetz mit Hilfe von Profilen Basierend auf Berechnungen fu¨r das U typischer Tage (“Typtage”) (s. Abschnitt 6.1.2 und 6.2.2 im Haupttext) ist langfristig dessen Erweiterung um etwa 3.000 km oder mehr notwendig, um der ra¨umlichen Verschiebung der Erzeugung aufgrund des substantiellen Anstiegs operativer Off-Shore-Windanlagen gerecht zu werden. Die Beschra¨nkung der Anlayse auf Typtage bedeutet, dass durch diese errechnete Erweiterung allerdings maximal nur etwa 70 Prozent der insgesamt installierten Windkraftleistung u¨bertragen werden ko¨nnen. In seltenen Extremsituationen, in denen die Leistung 70 Prozent der Maximalleistung u¨bersteigt, mu¨ssten daher Windkraftanlagen ¨ bertragungsnetz zu vermeiden. Fu¨r die abgeschaltet werden, um Scha¨den am U Abscha¨tzung der Werte wird außerdem angenommen, dass kein starker Austausch von elektrischer Energie mit Nachbarla¨ndern stattfindet. Andere Studien, die auch die netzseitige Abdeckung extremer Einspeisesituationen und einen starken Austausch mit Nachbarla¨ndern fu¨r die Abscha¨tzung des Ausbaubedarfs vorsehen, kommen zu einer Erweiterung von etwa 3.500 Kilometern, die bereits in 2020 notwendig sein werden. Unter Beru¨cksichtigung der derzeitigen und voraussichtlich zuku¨nftigen Entwicklung der Netztechnologien erscheint aus heutiger Sicht die Verwendung einer Kombination von konventionellen Drehstromfreileitungen mit Hochspan¨ ) am plausibelsten. Aus Rechnungen auf nungsgleichstromu¨bertragung (HGU Basis von Typtagen ergeben sich damit langfristig (2040+) Investitionskosten von sechs bis acht Milliarden € bzw. entsprechend etwa 0,2 bis 0,35 €-Cent pro kWh eingespeister Windenergie.

Hintergrund und Zielsetzung

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Wirtschaftspolitische Optionen fu¨r die Nutzung von Speichersystemen Die theoretische Analyse mo¨glicher Probleme einer Marktwirtschaft angesichts wetterabha¨ngiger Elektrizita¨tserzeugung und kulturell beeinflusster Nachfragefluktuationen (s. Abschnitt 7.1 im Haupttext) zeigt, dass mit dem Einsatz von Ausgleichstechnologien im Elektrizita¨tssystem verschiedene Nutzen verbunden sind. Durch die Verbesserung der Infrastruktur u¨ber nationale Grenzen hinweg ko¨nnten die Fluktuationen durch Lieferungen aus Regionen mit Angebotsu¨berschuss in Regionen mit Angebotsdefizit geda¨mpft werden. Sowohl Stromanbieter als auch -ha¨ndler ko¨nnten an dem Betrieb von Speichersystemen interessiert sein. Wa¨hrend Anbieter die Systeme voraussichtlich nahe der Erzeugung installieren werden, werden Ha¨ndler sie eher in Kundenna¨he platzieren. Netzbetreiber ko¨nnten Speicheranlagen idealerweise in Bereichen hoher Netzinstabilita¨t aufstellen. Allerdings ist es Netzbetreibern aufgrund der “Unbundling”-Richtlinie der Europa¨ischen Union derzeit nicht erlaubt Speicheranlagen in nennenswertem Umfang zu betreiben. Die Anwendung von Energiespeichern fu¨hrt zu einigen Systemverbesserungen, mit denen politische Eingriffe in den Markt gerechtfertigt werden ko¨nnen (s. Abschnitt 7.2 im Haupttext). Die Stabilita¨t der Energiebereitstellung wird erho¨ht, Umweltexternalita¨ten – vor allem die durch Klimawandel hervorgerufenen – werden reduziert, durch einen erho¨hten Anteil dezentraler Anlagen kann eine Monopolmacht in Zeiten knappen Angebots reduziert werden und die Anwendung von Technologien mit nicht versicherbaren Risiken (Kernkraftwerke) ko¨nnen reduziert oder im Fall von Deutschland ersetzt werden. Aufgrund historisch gewachsener Fo¨rderstrukturen werden andere Technologien im Energiebereich bereits staatlich gefo¨rdert. Daher ist derzeit aus praktischen Gru¨nden zusa¨tzlich eine Fo¨rderung von Ausgleichstechnologien notwendig, die u¨ber die der Forschung, Entwicklung und Demonstration hinausgeht.

Rechtliche Analyse der Rahmenbedingungen Einige der aktuellen regulatorischen Rahmenbedinungen sollten im Zusammenhang mit der Realisierung von Strategien zum Ausgleich von Nachfrage und Angebot elektrischer Energie bereits jetzt untersucht werden. Die rechtswissenschaftlichen Analysen in der vorliegenden Studie werden unterteilt in Aspekte zentraler Speichersysteme (Abschnitt 8.2 im Haupttext), dezentraler Speichersysteme inklusive Lastmanagement sowie “intelligenter” Netze (Abschnitt 8.3 im Haupttext) und der ¨ bertragungsnetzes (Abschnitt 8.4 im Haupttext). Die Ergebnisse Erweiterung des U sind im Folgenden dargestellt. Im Bereich zentraler Speichersysteme sollte sowohl im derzeitigen Recht als auch im noch zu gestaltenden Recht gekla¨rt werden, ob die Anwendung von Speichertechnologien der Erzeugerseite oder der Netzseite zugeordnet werden soll. Ihre rechtliche Klassifikation hat insbesondere Auswirkungen auf die Bewertung zivilrechtlicher Fragen wie z.B. die der diskriminierungsfreien Nutzung, des

xliv

Zusammenfassung

diskriminierungsfreien Zugangs und der Entflechtung (“Unbundling”). Es ko¨nnen verschiedene negative Anreize und Barrieren durch die derzeitige Gesetzgebung identifiziert werden, die Auswirkungen auf Investitionen in Speichertechnologien haben. Die in erster Linie betroffenen Akteure sind Erzeuger von Elektrizita¨t ¨ bertragungsnetzbetreiber, die aufgrund des aus erneuerbaren Energien und U Erneuerbare Energien Gesetzes (EEG) Strom aus erneuerbaren Energien kaufen und vermarkten mu¨ssen. Zusa¨tzlich ko¨nnte ein spezielles Planungsregelwerk fu¨r die Nutzung von Untergrundressourcen helfen, potentielle Konflikte zwischen den einzelnen Nutzern und zwischen Nutzern und den jeweiligen Landeigentu¨mern zu entscha¨rfen. Um die Entwicklung von Speichertechnologien nicht durch die Gesetzgebung zu behindern, sollten entsprechende negative Anreize beseitigt werden. Im Bereich dezentraler Speichersysteme, insbesondere bei der Elektromobilita¨t, intelligenten Netzen und allgemeiner beim Lastmanagement, mu¨ssen vertragliche Fragen in Verbindung mit ganz neuen Akteuren und Netzwerken hinsichtlich der Sorgfaltspflichten, Kooperation und Information sowie Nutzungsbedingungen beantwortet werden. Außerdem stellt sich durch die Mo¨glichkeiten, weitreichende und sehr detaillierte individuelle Profile der Mobilita¨t und Energienutzung zu generieren, die Frage, inwieweit die derzeitige Gesetzgebung im Bereich des Datenschutzes dazu geeignet ist, mit der Menge und Qualita¨t der Daten sowie mit den neuen Arten der Datenerfassung, -aufarbeitung und -nutzung legitim umzugehen. Neue Ansa¨tze fu¨r Lo¨sungen innerhalb und außerhalb des gesetzlichen Rahmens werden beru¨cksichtigt werden mu¨ssen. ¨ bertragungsnetzen sind sehr divers Derzeitige Verfahren fu¨r den Ausbau von U und in bestimmten Bereichen dysfunktional. Besonders problematisch erscheinen punktuelle Investitionspflichten von Netzbetreibern, die zivilrechtlich behandelt werden und bei denen gesamtwirtschaftliche Aspekte nicht ada¨quat beru¨cksichtigt werden (z.B. } 9 EEG). Hier wird ein umfassenderer und systematischerer Ansatz beno¨tigt. Auf nationaler Ebene ko¨nnte die Situation durch ein fundamentales ¨ bertragungsleitungen Reformmodell fu¨r strategische Investitionsprojekte in U verbessert werden. Einige Verbesserungen und Standardisierungen, z.B. in Bezug auf Richtlinien guter Praxis bei o¨ffentlichen Anho¨rungen, ko¨nnten den Umgang bei Konflikten mit der betroffenen lokalen Bevo¨lkerung verbessern. Die Mo¨glichkeiten fu¨r Reformen auf europa¨ischer Ebene sind begrenzt. Jedoch wa¨re eine bessere Koordination auf dieser Ebene sinnvoll.

Herausforderungen und Empfehlungen Die Anforderungen an den Ausgleich elektrischer Energie im System werden mit steigendem Anteil von Elektrizita¨t aus erneuerbaren Energien zunehmen. Allerdings zeigt die obige Zusammenfassung der Analysen in dieser Studie bereits, dass einige Herausforderungen mit der Nutzung alternativer Optionen, die niedrige CO2-Emissionen aufweisen, verbunden sind. Zu diesen geho¨ren Energiespeicher ¨ berinstallation der Erzeugungskapazita¨t inklusive Lastmanagement sowie die U

Hintergrund und Zielsetzung

xlv

zusammen mit einem entsprechenden Netzausbau. Zur Gewa¨hrleistung einer stabilen Elektrizita¨tsversorgung mu¨ssen dabei die verschiedenen Standorte in Europa und die relevanten Zeitskalen von Sekunden zu Tagen und Wochen beru¨cksichtigt werden. Im Folgenden werden die 13 identifizierten Herausforderungen mit entsprechenden Empfehlungen, die aus der Studie abgeleitet wurden (s. Abschnitt 9.2 im Haupttext), zusammengefasst aufgelistet. Herausforderung 1: Bereitstellung ausreichender Speicherkapazita¨t in Deutschland – Ein Mix verschiedener Speicheroptionen, der auf die Netzrestriktionen abgestimmt ist, sollte installiert werden um die Abschaltung von Windkraftanlagen in der Spitzenerzeugung zu verhindern und die Anwendung von kohlenstoffarmen Alternativen zum Schließen von Angebotslu¨cken zu ermo¨glichen. – Internationale Netzwerke sollten etabliert werden, um große Speicherpotentiale in einigen europa¨ischen La¨ndern weiterzuentwickeln und nutzbar zu machen. – Die U¨berinstallation der Kapazita¨t von Wind- und Solar-Kraftwerken ¨ bertragungskapazita¨t zusammen mit der Gewa¨hrleistung ausreichender U sollte als Option beru¨cksichtigt werden. – Alternative technische Optionen, wie etwa die Nutzung der Gasnetze fu¨r die Speicherung von Energie, sollten weiter analysiert werden. – Negative Anreize in der rechtlichen Regulierung sollten beseitigt und in Zukunft vermieden werden. – Forschung, Entwicklung und Demonstration der Technologien sollten intensiviert werden, um die Kosten der Speichertechnologien zu reduzieren.

Herausforderung 2: Realisierung technischer Potentiale dezentraler Optionen – Automatisierte technische Lo¨sungen fu¨r die Steuerung von Lasten sollten entwickelt werden, um Minderungen im Nutzungskomfort zu vermeiden. – Flexible Tarife sollten eingefu¨hrt werden, um die Wahrnehmung von Knappheiten und tempora¨ren Variationen im Wert elektrischer Energie zu steigern. – Datenanforderungen fu¨r Steuerungsvorga¨nge sollten minimiert und ada¨quate Datenschutzbestimmungen eingerichtet werden. – Forschung, Entwicklung und Demonstration fu¨r die Standardisierung sollten vor allem im Bereich automatisierten Lastmanagements weiter vorangetrieben werden.

xlvi

Zusammenfassung

Herausforderung 3: Management der Umwelt- und Ressourcennutzung – Durch eine geeignete Gestaltung der Technologien sollten potentielle Hemmnisse durch die limitierte Verfu¨gbarkeit beno¨tigter Ressourcen oder durch das Auftreten von Umwelteffekten bei Massenbedarf bereits fru¨hzeitig beru¨cksichtigt werden. – Kontinuierliche Beobachtungen der Ressourcennutzung und der Ma¨rkte wa¨hrend der Entwicklung sollten erfolgen. – Forschung, Entwicklung und Demonstration in den Bereichen Recycling von Sekunda¨rrohstoffen und Substitute sollte erfolgen und wo notwendig sollten entsprechende Prozesse eingerichtet werden. Herausforderung 4: Bereitstellung ausreichender Netzwerkkapazita¨ten fu¨r den Transport von Elektrizita¨t – Eine Beschleunigung von Planungsprozeduren sollte durch die Einfu¨hrung strukturierter Mechanismen erreicht werden. – Eine Sta¨rkung der nationalen und europa¨ischen Interessen im Verha¨ltnis zu regionalen Interessen sollte u¨ber die Reformierung des Regulierungssystems erreicht werden. – Forschung und Entwicklung sollte durch den Regulator unterstu¨tzt werden, indem die entstehenden Kosten im Rahmen der Kostenerstattung akzeptiert werden. Herausforderung 5: Ada¨quate Beru¨cksichtigung von Ausgleichsstrategien in Regelwerken – Zuordnungen und Definitionen im Zusammenhang mit Ausgleichstechnologien sollten in den entsprechenden Regelwerken gekla¨rt werden. – Entscheidungen u¨ber die Zuordnung von Speicheranlagen zur Netz- oder zur Erzeugungsebene sollten vom Gesetzgeber getroffen werden. Herausforderung 6: Gestaltung eines europa¨ischen Energiemarkts ¨ bertra– Austausch von Elektrizita¨t sollte ermo¨glicht werden, indem das U gungsnetz weiter ausgebaut wird. – Ein Rahmen fu¨r eine kohlenstoffarme Energieversorgung sollte fu¨r Europa implementiert werden, der umfassend, langzeitorientiert und weitreichend bzw. ehrgeizig ist und u¨ber 2020 hinaus geht. – Europas Elektrizita¨tsma¨rkte sollten weiter integriert werden.

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Herausforderung 7: Beseitigung u¨berholter Subventionen und Steuern – Optimale o¨konomische Rahmenbedingungen sollten hergestellt werden, indem u¨berholte Subventionen und Steuern schrittweise zuru¨ckgenommen und konsistente Maßnahmen wie Demonstrationsprojekte und zeitlich beschra¨nkte Startsubventionen eingefu¨hrt werden. – Historisch gewachsenen Misssta¨nden in den Rahmenbedingungen sollte durch zeitlich begrenzte Subventions- und Steuerausgestaltungen begegnet werden. Herausforderung 8: Umwandlung von Markt-Externalita¨ten in Kosten und Erlo¨se – Sozioo¨konomischer Nutzen sollten internalisiert werden, indem entsprechende Ma¨rkte und Kompensationsmechanismen eingerichtet werden. – Kosten von Systemdienstleistungen sollten internalisiert werden, indem Mechanismen eingefu¨hrt werden, u¨ber die Stromerzeuger fu¨r die geleisteten Dienstleistungen, die sie fu¨r einen reibungslosen Betrieb der Kraftwerke beno¨tigen, inklusive der Netze, zahlen mu¨ssen. – Vorteile durch Koordination der Produktion von Elektrizita¨t aus erneuerbaren Energien mit dem Netzmanagement und der Nutzung von Speichern sollten im Hinblick auf die Realisierung zusa¨tzlichen Nutzens untersucht werden. – Mo¨gliche Gescha¨ftsmodelle sollen im Detail analysiert werden. – Detaillierte Systemanalysen von Nutzen durch die Anwendung von Ausgleichsstrategien sollten als Basis fu¨r Politikentscheidungen durchgefu¨hrt werden.

Herausforderung 9: Handhabung neuer komplexer Marktstrukturen – Vertragliche Herausforderungen auf neuen Ma¨rkten sollten im Detail analysiert werden. – Generelle rechtliche Maßnahmen fu¨r neue Ma¨rkte sollten entwickelt werden. Herausforderung 10: Sta¨rkung wissenschaftlicher Beratung im Bereich der Ausgleichsstrategien – Die Energiesystemanalyse sollte durch intensive Forschung mit umfassenden Modellen und unter der koordinierten Kooperation relevanter Institutionen verbessert werden.

xlviii

Zusammenfassung

– Großprojekte zur Energiesystemmodellierung sollten durchgefu¨hrt und Vorteile ihrer Institutionalisierung, die regelma¨ßige Aktualisierungen und Beobachtung der Systementwicklungen erlauben wu¨rde, untersucht werden. – Die europa¨ische Perspektive, unter der Beru¨cksichtigung nationaler Politiken, sollte fu¨r eine erweiterte Energiesystemanalyse verpflichtend sein. – Die beno¨tigte installierte Leistung und Energiekapazita¨t sollten in zuku¨nftigen Studien als Hauptaspekte im Detail analysiert werden. Herausforderung 11: Ada¨quate Unterstu¨tzung der Verwendung neuer Technologien – Startsubventionen sollten eingefu¨hrt werden, die auf Marktmechanismen basieren, und automatisch auf das Niveau der Kompensation von Externalita¨ten abgesenkt werden, um die Verwendung vielversprechender Technologien ada¨quat zu fo¨rdern. – Investitionen in Forschung, Entwicklung und Demonstration fu¨r Speichersysteme sollten erho¨ht werden. Herausforderung 12: Ada¨quate Unterstu¨tzung von Langzeitinvestitionen – Politische Entscheidungen u¨ber Rahmenbedingungen auf nationaler und internationaler Ebene sollten zuverla¨ssig und langfristig sowie in ¨ bereinstimmung mit der europa¨ischen Wettbewerbspolitik festgelegt U werden. – Eine verla¨ssliche Basis fu¨r Entscheidungen u¨ber Rahmenbedingungen sollte durch erweiterte Energiesystemanalysen geschaffen werden.

Herausforderung 13: Umgang mit Konflikten bei Großprojekten – Ada¨quate Mechanismen fu¨r die Beteiligung betroffener Parteien und der ¨ ffentlichkeit im Entscheidungsprozess sollten eingerichtet breiteren O werden. – Die Einrichtung eines speziellen Planungsregelwerks fu¨r Untergrundressourcen sollte auf ihr Potential zur Vermeidung mo¨glicher Konflikte der relevanten Interessengruppen hin analysiert werden. – Maßnahmen zur Konfliktlo¨sung wie die Gewa¨hrung ada¨quater Kompensationsmaßnahmen sollten weiter analysiert und, wo sinnvoll, angewandt werden.

1

Introduction

1.1

Background

The industrial revolution led to a technological and energy transformation in Europe. Economies that through the end of the nineteenth century had been primarily driven by coal and small-scale renewables diversified their energy mix and became increasingly dependent on oil, natural gas, medium- and large-scale hydropower and nuclear energy. Since the beginning of the 1970s, it has become increasingly clear that resource and environmental constraints significantly influence economic activities and can limit economic growth if not managed satisfactorily. Importantly, the publication of the Club of Rome report, Limits to Growth (Meadows et al. 1972) injected economic theory and modelling into the discussion of natural resource use. This book does the same in relation to a low-carbon European electricity future. Europe needs to find a new approach to the energy structures that are the backbone of its economic growth and development. The energy sources that made the technological transformation of the past century possible are for the most part non-renewable. Coal is the only fossil fuel that still remains in some abundance in Europe, however, it is heavily polluting. New sources of natural gas are being explored and new retrieval methods are being developed, but demand could easily outstrip supply in the future. Irrespective of whether peak oil is in fact already here, is likely to occur in the near future, or will not happen until sometime in the next century, the long-term consequences remain the same: fossil fuel supplies are limited and non-renewable. There is a further argument for an energy revolution. The dependency of the European Union on imports of energy resources has increased substantially over the past years. With growing global demand for energy and declining domestic reserves in the EU, competition for easily accessible remaining supplies is becoming more intense. Energy prices in Europe are likely to continue to rise. Political instability in oil-rich regions, as can be seen in the Arab world, can accelerate these processes.

B. Droste-Franke et al., Balancing Renewable Electricity, Ethics of Science and Technology Assessment 40, DOI 10.1007/978-3-642-25157-3_1, # Springer-Verlag Berlin Heidelberg 2012

1

2

1

Introduction

Even more pressing than these resource constraints are the environmental constraints tied to the heavily fossil-fuel based economies of Europe and other regions of the globe. Climate change attributed to anthropogenic emissions of greenhouse gases is regarded as the most serious potential environmental impact of fossil fuel use. The Intergovernmental Panel on Climate Change (IPCC) and many other bodies warn that the emissions from fossil fuel burning are contributing to a warming of global average temperatures and putting the planet at risk of severe weather extremes. The change in the climate of the planet could affect seasonal temperatures and rainfall patterns, turning some parts of Europe into desert-like regions. The melting of polar ice and glaciers could contribute to sea level rise. More severe storms and hurricanes and periods of excessive heat and drought are also predicted (IPCC 2007) and can be observed already in many parts of the world. Due to insufficient knowledge about natural processes and uncertainties related to future developments, none of these effects can be predicted with high accuracy. Theoretically, it is not possible to prove strictly that climate change is caused by human beings. Nevertheless, there are strong indications that anthropogenic emissions are influencing the climate. Given that the potential impacts of climate change could be very severe, at the United Nations Conference on the Human Environment, the international community determined it necessary to begin to take measures to reduce greenhouse gas emissions and limit the potential socio-economic impacts of climate change to acceptable levels. A first step in this process was the formulation of the Kyoto Protocol. Based on the precautionary principle, the Kyoto Protocol introduced concrete reduction aims for greenhouse gas emissions. The agreement runs through 2012. Negotiations on a possible follow-up agreement continue, but obstacles remain large. Carbon dioxide (CO2) has been identified as the major anthropogenic greenhouse gas. It is the main end product of processes in which fuels with carbon content are burned. It is for this reason that processes of energy conversion from fossil fuels are a main focus of measures to reduce the extent of anthropogenically induced climate change. One way to reduce CO2 emissions is to install energy conversion plants that make use of continuous natural energy fluxes to the Earth instead of fossil-stored energy. This can be done by converting solar radiation directly, or by using it indirectly via kinetic wind and wave energy or via produced biomass to produce electricity and heat. An extensive use of such renewable energies is seen as a promising, and largely undisputed path to a viable energy system. For this reason, renewable energy is being promoted by many governments as a major measure for curtailing climate change. Renewable energy can contribute substantially to solving climate change problems, addressing resource depletion, and reducing dependency on international energy resources. More than in any other region in the world, Europe is taking the lead on renewable energy and especially wind and direct solar radiation. Economic and technological potentials and scenario analyses point to the importance of these renewable resources. Throughout Europe, as well as at the European Union level, politically set targets are promoting the rapid growth of the use of kinetic energy for electricity production, particularly from wind and direct solar radiation.

1.2

Renewable Energies in the European Energy Mix

3

Yet, as the availability of these energy sources is very dependent on weather conditions, their use presents challenges. Weather dependent fluctuations in supply can seriously impact the provision of electrical power. To ensure a stable electricity supply, the distribution of electricity via the grid requires that total input and output is equal at all times, even in the scale of seconds. In order to assure this, the current energy system uses a sophisticated system for balancing energy and power. However, the existing grid structure is coming under growing strain, as it was not designed for large-scale renewable energy use. Two different kinds of problems can occur. On the one hand, there may be insufficient electricity provision from renewable energies as a result of long periods of cloudiness or darkness or insufficient wind. When this happens, backup systems (currently, these would typically be high-carbon options such as coal or natural gas powered utilities) that can fill the gap in supply are required. In other cases, the supply from renewable energies can exceed demand. In these cases, under current regulations and market conditions, negative prices can occur on the market. This is clearly a negative and inefficient outcome and suggests a problem with the existing electricity infrastructure in Europe. Expanding energy storage capacities and network structures will prospectively be a better alternative with a larger amount of power from renewables in the system than the current strategy for dealing with such situations, which is essentially to simply turn off wind turbines or disconnect wind and photovoltaic systems from the grid. Most studies addressing future energy systems need to concentrate on energy conversion issues without giving much attention to the multiple options that exist for auxiliary systems and balancing strategies. Little attention has been given to new technology development needs or to the planning and approval processes tied to the modernisation and extension of electricity networks. This study aims to take on this important challenge by exploring and analysing alternative strategies and technologies that can balance gaps between supply and demand that can be created by unsuitable weather conditions. The authors recognise that this is a challenge that will require several years but is critical to the development of a low-carbon electricity supply for Europe.

1.2

Renewable Energies in the European Energy Mix

The share of renewable energies (wind, solar, biomass, hydro) in the EU’s energy mix has basically doubled in the first decade of the 2000s, from about 5% in 2000 to over 10% in 2008. The EU’s recent efforts to strengthen renewable energy policies are tied both to growing concerns about the EU’s energy import dependency and to climate change. As renewable energies are relatively non-controversial, can be domestically developed, and are also climate-friendly, there has been a big push to promote renewables within the EU in recent years. EU renewable energy policies are a way of moving member economies towards greater energy autonomy, resource efficiency and technological progress. Various plans are being laid for

4

1

Introduction

how the EU can shift from its still heavily fossil-fuel based electricity structure towards a lower-carbon supply. There was a steady growth in energy consumption in Europe until about 2003. Since this time, consumption has largely stabilised. Europe remains heavily dependent upon fossil fuels for its primary energy, but a clear shift in the energy mix over time is becoming visible. According to Eurostat, in 1998, crude oil, petroleum products, and solid fuels combined accounted for 59% and renewables a mere 2% of gross inland consumption. A little more than a decade later, in 2008, crude oil, petroleum products, and solid fuels still accounted for 54% of the total energy consumption mix, while renewables increased their share to 10% of gross final energy consumption (Eurostat 2011a). The European Union is a net energy importer. Its dependence on fossil fuel energy imports has increased from 46% in 1998 to 54% in 2009 (see Fig. 1.1). With growing demand for energy resources and minerals coming from emerging economies (e.g., China, India, South Africa, Brazil), expectations are that energy prices will rise, hurting European economies. Thus, the incentive to diversify energy supplies and increase domestic production is becoming stronger. EU-27 domestic electrical power production in 2008 can be seen in Fig. 1.2. Renewables add up to 18.3% in total, which is more than the individual contributions of hard coal, lignite and crude oil (Eurostat 2011c). Thus, in terms of what the EU can domestically produce, renewable energy holds a substantial share. It is also one of the energy sources that can be most easily expanded in Europe. Furthermore, the development of new production capacity has been dominated by the renewable energy sector, and particularly biomass and waste to energy. There was a 38.4% production increase in renewable energy production capacity between 2002 and 2007. During the same time frame production of other energy sources fell: crude oil ( 28.7%), natural gas ( 18.1%), and solid fuels ( 11.1%). The developments in the energy sector show that the electricity mix is already changing with continuously increasing shares of renewable energies (see Fig. 1.3). Additionally, the EU has defined a target for 2020 that 20% of energy consumption should be provided by renewable energies. This implies that besides heat production, the share of electricity produced with renewable energies will increase significantly in Europe in the coming decade. Some countries within the EU have established even more ambitious targets. For example, the German “Energy Concept for an Environmentally Sound, Reliable and Affordable Energy Supply” states as one target to raise the share of renewables in the gross energy consumption to 60% and of gross electricity consumption to 80% by 2050. Some studies even discuss the possibility of establishing a 100% renewable electricity supply for Germany (e.g., Umweltbundesamt 2010; SRU 2011) or Europe (e.g., PwC et al. 2010) by 2050. The examples of countries such as Germany or Denmark which have relatively high shares of power produced from fluctuating renewable energies hint at the upcoming challenges the European power sector is likely to face. Electricity production and distribution in these countries show that with using fluctuating sources of energy for electricity production such as wind and solar radiation,

1.2

Renewable Energies in the European Energy Mix

5

Fig. 1.1 European energy dependence (percentage total) (Source: Eurostat 2011e)

Total production: 812 million toe

renewables 18.3%

coal and lignite 20.4%

crude oil 12.8% nuclear 28.4% natural gas 18.8%

Fig. 1.2 EU 27 total primary energy production by source (Source: Eurostat 2011c)

large gaps can occur in the provision of electricity. This can lead to blackouts if the gaps are not filled by backup technologies. These can be either other forms of installed power or storage capacities. As an example, Fig. 1.4 shows the power that is provided during a period of several days of wind calm in the Vattenfall electricity grid in Germany. This represents the eastern control area of the country. A total shortfall of about 540 GW h electrical energy can be observed. From a further look at the details of the time curve, it is obvious that balancing activity is also required

6

1

Introduction

3000

[1000 toe]

2500 2000 1500 1000 500 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 Year

Power in MW

Fig. 1.3 Renewable energy (primary production) (Source: Eurostat 2011f)

Load curve

Wind power

Wind power prognosis Pumped hydro storage systems in Germany 40,000 MWh 7,000 MW IfR, TU Braunschweig

Weeks in 2008 (calendar dates)

Fig. 1.4 Load and wind power, predicted and produced, in the German high-voltage grid (eastern control area) (01/02/2008–06/03/2008) (Based on the source: IfR/TU Braunschweig, taken from (B€ unger et al. 2009:13))

on a shorter time scale of minutes to some hours in order to cover the discrepancy between the energy-meteorological prognosis and actual power production. This data from the German eastern control area illustrates convincingly some of the major challenges for balancing energy and power when there is a high penetration of renewables in the electricity system. Compared to the currently installed aggregated storage capacity of pumped hydropower plants of 90 GW h worldwide and 40 GW h in Germany, which represent by far the highest potential for storing electricity, it becomes clear that currently only conventional power plants can cover such gaps. It is also important to

1.3

Aim and Structure of the Study

7

realise that backup power plants produce power at relatively high costs if they are needed only a small number of hours per year. This will particularly be relevant when new plants have to be built. Furthermore, restrictions in CO2 emissions, as well as future prices for natural resources and investments, may increase the costs even more or even lead to a phase-out of such power plants for backup purposes. A further consequence of future prices and policies may be an extension of transborder infrastructure for electricity transport. Currently, international European trade in electricity is limited. Expanding interconnections in Europe could improve conditions and increase aggregate welfare.

1.3

Aim and Structure of the Study

The current study is based on an interdisciplinary analysis of strategies for balancing out demand and supply of electricity in situations where there is a high share of wind and solar power in the energy system. To enhance the practicality of the study, not only technical and economic aspects, but also political and legal framework conditions are investigated. The analyses in the different sections culminate in recommendations for action, which the authors argue should be taken to open up opportunities for future options in the area of balancing strategies. In the study the status quo of legal regulations of April 2011 is assumed. In the first part of the study (Chap. 2), perspectives for a future electricity system are discussed from normative economical, political and technological perspectives. At first, general aims for the long-term viable development of energy systems are discussed and indicators for characterising and evaluating balancing strategies are derived. Very significant for the development of the electricity system will be the current and future national and international energy policies with respect to climate change. This discussion is followed by an economic analysis of storing values of electrical energy. This analysis is carried out to reveal options for balancing electricity supply and demand in a system with a high share of electricity produced from wind and solar radiation. In Chap. 3, existing future energy scenarios are analysed and characterised in order to evaluate their applicability to this study. Finally, based on selected scenarios, parameters are derived which can consistently be used as input for the analysis of balancing strategies in the following parts of the study. In Chap. 4, the prospective demand for balancing electrical energy and power is estimated, relying on the parameters extracted from the selected future energy system scenarios. Two approaches are followed. The first assesses the balancing activities required to realise a certain demand and supply structure analogous to a potential target scenario, by assuming the current energy distribution system. The second sets up a completely new infrastructure of energy storage systems and electricity networks as a result of an optimisation process, including the distribution of wind power and photovoltaics over Europe on the basis of hourly weather data covering seven consecutive years. First analyses were performed. In order to investigate situations with high challenges for strategies of balancing electricity

8

1

Introduction

supply and demand, in both cases scenarios with a high share of renewable energy in the system were chosen. In Chap. 5, technological options for balancing electrical energy and power are discussed. For a better description and analysis of the options, a system for characterising the technologies is developed. In order to discuss the potential future competitiveness of the application of storage technologies, costs are analysed for specific tasks. Additionally, various technological options for a stable energy system are analysed with respect to their environmental effects, resource use and system characteristics. This is done in order to assess their future viability. Impacts of the technical changes on the energy networks are analysed in Chap. 6. In addition to an examination of technical-economical barriers, including network requirements, the costs of the network extensions required to make possible balancing activities at daily and seasonal scale are addressed. Chapter 7 discusses potential benefits from storage systems, as well as problems in their realisation. Furthermore, reasons and options for changing economic framework conditions are analysed. This analysis results in economic recommendations for future energy policies. Chapter 8 concentrates on important legal aspects which could hamper centralised and decentralised energy storage systems as well as the required network expansions, using locally relevant technologies such as the smart meter and smart grid as well as regional extensions of transmission lines. Planning and licensing procedures, regulatory incentives, access, unbundling, contractual relationships in large networks, and data protection are identified as important areas for the analysis. The barriers for the future development of an energy system, including the required storage and electricity network capacities identified in the previous chapters, are summarised and concluded in Chap. 9. As a major result of the study, a list of recommendations is derived from the analyses found in the previous chapters. Many of the concepts for an energy system with a high share of renewable energies only make sense on the European scale, where it is possible to efficiently make use of the geographically varying potentials of various renewables, such as intense solar radiation in the southern part of Europe and high wind speeds on the coasts and in elevated areas. It is on the geographical scale of Europe that the most interesting analyses of energy systems that are able to balance energy supply and demand can be made. Theoretically, it is at the European level that renewable energies can most effectively be distributed, including through the import and export of electricity and the use of storage facilities in local areas. Current reality shows, however, that European nations still cling to their sovereignty when it comes to the most relevant energy questions. Thus, there is still no true European energy system or energy market in practice. This means that some issues have to be analysed on the national level, whereas other aspects require a European scale. Analysing all national aspects for all nations in Europe is, however, far beyond the scope of this study. Instead, the focus is placed on Germany as an example of a country with very ambitious aims for the integration of renewable energies in Europe. The German situation is analysed in consideration of the background and influence of the European context.

2

Future Perspectives of Electrical Energy Supply

In order to describe the future perspectives of a renewable-dominated electrical energy supply system that will be stable over the long term, first, goals must be established (see Sect. 2.1). Based on these aims, in Sect. 2.2, indicators which can be applied to evaluate and decide upon technological options are discussed. The theoretical background of the renewable energy aims and indicators is supplemented in Sect. 2.3 by the analysis of the current and potential future aims of energy and environmental politics with respect to the energy system. This section points out some of the political challenges that need to be addressed. Finally, the economics of storage system values is discussed, showing that there is an economic motivation to store electricity (see Sect. 2.4).

2.1

Aims for a Long-Term Viable Development of a Renewable-Based Electricity System

The concurring targets of the energy economy are often shown as a triangle of efficiency, supply security and environmental compatibility. It has become increasingly obvious that the current electricity system is incompatible with environmental protection requirements. When reconstructing the electricity systems, the supply security and environmental compatibility targets of the triangle have to be given adequate consideration as well. Ideas for developing such a system can be taken from economic analyses of overall societal efficiency and sustainability.1 These are taken here as a basis for the evaluation of the future viability of various technologies for the electricity system as well as of the system itself. The argumentation is based on work done in Droste-Franke et al. (2009) and Droste-Franke (2005). A more detailed discussion of the individual issues can be found there.

1 Sustainability is used here as specific concepts for maintaining societal assets in the context of ensuring a just intergenerational distribution following de Haan et al. (2008).

B. Droste-Franke et al., Balancing Renewable Electricity, Ethics of Science and Technology Assessment 40, DOI 10.1007/978-3-642-25157-3_2, # Springer-Verlag Berlin Heidelberg 2012

9

10

2.1.1

2 Future Perspectives of Electrical Energy Supply

Efficient Allocation and Just Distribution

The fundamental elements of economic action can be reduced to the attribution of existing means to applications (allocation) and to individuals (distribution). In the context of the overall economy, respective economic aims are expressed as efficient allocation and just distribution among current individuals at the present point in time, as well as in the future, between generations living at different time periods. These concepts are known as intra- and intergenerational distributive justice. From a macro-economic point of view, the efficiency of an economy is linked to optimising the welfare of a society as a whole (cf. Schumann 1992). The optimum is derived as a so-called pareto-optimal state in which nobody’s utility can be improved without somebody else’s utility being degraded. Assuming the conditions of an ideal market and basic assumptions about the preferences of individuals, it can be theoretically proven that an equilibrium of supply and demand on the markets leads to such a pareto-optimum (see Malinvaud 1972). Therefore, the aim of economists is to achieve market conditions that are close to perfect so that trading on the markets leads to a pareto-optimum. A presupposition for this is that market failure, which can be caused by market power, badly regulated ownership rights or imperfect market structures is avoided. For the equilibrium it is furthermore important that it is stable; otherwise it will not be reached. In order to achieve intra- and intergenerational distributive justice, the concept of sustainable development has been applied in economic analysis. Quoting the most-cited definition given in the so-called Brundtland report, sustainable development means to implement a “development that meets the need of the present without compromising the ability of future generations to meet their own needs” (WCED 1987, p. 43). As no information about the needs of future generations exists, for the operationalisation of the concept, it is assumed that future generations have the same needs as the current generation. The goal is to install a type of economic development that ensures that the needs of future persons having identical needs to the persons living today can be satisfied continuously. Development will require monitoring and sufficient flexibility to be able to adjust to changing preferences. Furthermore, the definition does imply that it must not be accepted that future generations may not be able to satisfy their needs (that are assumed to be equal to the needs of the contemporary generation). Thus, the implementation of the precautionary principle in order to avoid inacceptable risks is implicit in the Brundtland definition. The concept of capital2 and assets are critical to this discussion. Capital must be preserved to such an extent that the needs of future generations can still be met. One sub-target is to sustain the total value of the available capital. An equivalent formulation is that the rents obtained from the usage of natural resources must be

2 Capital is used here as generic term for objects which can be used for the production of economic income. This includes beside others produced and natural capital.

2.1

Aims for a Long-Term Viable Development of a Renewable-Based Electricity System 11

re-invested into reproducible capital (Nutzinger and Radke 1995, p. 32). This concept is called “Solow-Hartwick” sustainability or “weak” sustainability. Following the definition of the Brundtland report, for an economic development to be sustainable means that no actions must be taken that could risk the loss of capital and jeopardise the ability of future generations to satisfy their needs. This requires using natural capital in such a way that it will still be available in the future. In order to guarantee this, it is not sufficient to follow the concept of weak sustainability, because some types of natural capital are not substitutable. An often discussed interpretation of the requirements for the adequate protection of natural capital is that its functions have to be preserved. This can be ensured by producing functional-equivalent capital providing the functions to the extent they are on the other side degraded or depleted respectively. Preserving the functions can directly be applied as a principle for the usage of non-renewable resources. Capital is characterised as essential or “critical natural capital” (see Neumayer 1999, p. 27), if it is not substitutable and its reduction to below a critical level could lead to the loss of fundamental life-support functions or mean irreversible destruction resulting in an unacceptable environmental status. The concept can be operationalised by defining limits that ensure that unacceptable risks are avoided, even in situations of risks with high potential impacts, inadequate evaluation because of uncertainty, and lack of knowledge about impacts. Environmental areas in which a critical burden could occur are: climate change, ozone layer depletion, dispersion of toxic substances, and pollution of ecosystems, among others. Another term for this concept is “critical sustainability”.

2.1.2

An Operative Action Rule

The different aims of economic efficiency and distributive justice in its various facets can be combined in the following action rule formulated in the form of four priorities (see Droste-Franke 2005; Droste-Franke et al. 2009): Priority 1. Protection from unacceptable damage through compliance with critical limits of load Critical stocks of each relevant societal asset component3 must not be under-run. Priority 2. Preservation of the total value of produced and natural capital Provided that priority 1 is met, adequately evaluated changes of all relevant societal asset components must add up, at minimum, to zero. In the case that priority 1 can only be reached with a negative balance, this must be minimised.4

3

These include, among other things, natural assets, e.g., ecosystems. The stocks can principally be measured in arbitrary units. 4 This addition is introduced in order to cover the case in which the efforts for guaranteeing the protection from inacceptable damage are so great that a reduction of total assets is necessary. An equivalent formulation is: In the case that priority 1 cannot be reached without a negative balance, the maximum level of societal assets must be aimed for, so that a balance of zero can be reached.

12

2 Future Perspectives of Electrical Energy Supply

Priority 3. Maximising intertemporal welfare The present value5 of the intertemporal benefit must be maximised, thus achieving priorities 1 and 2. Priority 4. Just distribution of basics at present The basics for meeting needs, resulting after achieving priorities 1–3, must be justly distributed within and between societies and generations according to societally defined rules. The agreed critical loads for the preservation of critical assets in this context are to be seen as a result of societal processes in which the acceptability of potential impacts from the respective environmental burden is discussed. Discussions for fixing these values build on scientific findings from the corresponding environmental areas. Should new knowledge arise with regard to the values of the critical limits, the costs for achieving the limits, or the impacts occurring if limits are exceeded, then the formerly agreed critical values should be adjusted respectively. The formulated action rule represents a normative frame, which has to be filled with content. In many areas, critical values are not fixed or are still being discussed. Furthermore, the discussion about what has to be preserved and to what extent enters the models, for example, in the form of different assumptions about rates for discounting future impacts and benefits. In areas for which societal agreements exist about critical limits that have to be met, the presented rule provides a possibility for consideration. This can practically be done through, for example, formulating restrictions for the welfare optimisation process. Restrictions, according to priorities 1 and 2, are particularly important if not all relevant aspects can be evaluated adequately in monetary values or if relevant non-linear effects cannot be sufficiently considered in the optimisation process.

2.2

Indicators for the Evaluation of Balancing Strategies

In order to characterise the purposes relevant for a long-term viable development of the energy system, a classification scheme of Steger et al. (2005, p. 54) which distinguishes between three categories is followed in the analysis: – protection of the environment, – availability of resources, – design of the energy system with respect to society. While the availability of resources concerns the inputs available for production, the protection of the environment aims at conserving the assimilation capacity and the life-supporting functions of the environment. The way the energy supply system is organised comprises direct influences of the system via its embodiment in society.

5 By using the present value of the benefit as a uniform value, present prices are used and future benefits are expressed by discounting them to get the present values.

2.2

Indicators for the Evaluation of Balancing Strategies

2.2.1

13

Indicators for Environmental Effects

In evaluating the environmental effects of energy systems, emissions of chemical substances are relevant. Direct emissions of noise and radiation are of less importance, but are also considered if relevant. For the categorisation of relevant substances, characteristics regarding the environmental dispersion, the chemical transformation and the relevant environmental impacts are consulted. The first category resulting from these perspectives is represented by chemical pollutants that directly affect organisms and materials via chemical reactions and mechanical impacts. Amongst other impacts, these lead to harmful effects on ecosystems, crops, materials and human health. Pollutants for which harmful impacts are observed even at very low concentration levels are called toxic substances. Particularly important in this context are substances with long lifetimes, which may accumulate in the environment. Major representatives are heavy metals, persistent organic pollutants and radio-nuclides. Furthermore, optical influences of the atmosphere, such as opacity, can be observed, particularly due to the emission of fine particles and their precursors. Another relevant effect that is currently dominating the discussion of environmental impacts is the emission of gases, which increase the so-called greenhouse effect of the atmosphere. They have an influence on the radiation budget of the Earth by absorbing radiation from the ground in the infrared frequencies and re-emitting partly to the Earth. This effect results in a long-wave counter radiation, causing a higher temperature at ground level than would be observed without these gases. Increasing the natural concentration of the greenhouse gases as well as emitting further gases showing a similar effect on the radiation balance, lead to higher average temperatures and climate change effects. Important are particularly gases absorbing at so far vacant frequencies in the infrared area. The complete effect of the gases typically unfolds only after some years. Not of central importance to this study, but also of relevance, are gases that contribute to the stratospheric depletion of the ozone layer. As already mentioned in the section dealing with the design of the energy system, by following the four priorities in the action rule, two types of risks have to be distinguished: first, risks with limited potential for damage in the areas of human health and produced or natural capital and second, risks that result in large unacceptable damages. In the case of marginal or small damages to the environment, the evaluation is ideally carried out by quantifying the utility losses caused by environmental and human health impacts. For the evaluation of utility losses and external costs from energy systems, the impact pathway analysis has been established within the ExternE project series, which began in the early nineties (European Commission 1995, 1999, 2005a). Starting from the emission of substances, the physical impacts on the environment and human health are estimated by modelling the dispersion and chemical transformation. Based on these estimates, the related utility losses are quantified in monetary terms as far as possible. The uncertainties in the estimates increase with each further step in the impact pathway. If high uncertainties exist in

14

2 Future Perspectives of Electrical Energy Supply

parts of the pathway, intermediate indicators like for example, the amount of emissions, concentration increase or additional physical impacts can be consulted additionally or alternatively to the monetised costs for the evaluation of risks arising from energy systems. The impacts that will be analysed from this area are: – impacts on human health, material damage, crop loss and biodiversity loss caused by environmental pollution, – various relevant marginal impacts from climate change. In the area of risks with potentially inacceptable impacts, agreed critical limits should be met. This aspect has already been discussed in the evaluation of the energy system design. Critical limits are defined for many indicators from the respective impact pathway. These can be the amount of emissions, concentration levels or environmental flows, such as the deposition rate of substances. In the case of greenhouse gases, for instance, targets agreed upon for emission reductions in order to avoid potential unacceptable damage, e.g., those required for meeting the two-degree aim, can be interpreted as critical limits. For the aggregation of effects from different emissions, substances with the same impact can be normalised by estimating the relative share of the individual contribution to the respective total impact. In the case of greenhouse gases, for instance, CO2 is taken as a reference and emissions of all gases are usually expressed in CO2 equivalents. In the case of acidification and eutrophication problems, first, concentration levels and deposition values have been taken as a basis for politically fixed limits to the environmental burden. These have then been translated into amounts of emission reduction, which form the foundation for international agreements, e.g., the Gothenburg protocol and related declarations. Impacts considered with respect to critical limits are: – eutrophication and acidification due to environmental pollution, – land use, – depletion of the stratospheric ozone layer, – greenhouse effect. Some of the environmental aspects are mentioned for both areas, small and large potential damages. However, the subjects of analysis differ between the two types of risks.

2.2.2

Indicators for Resource Availability

For the evaluation of resource use, it is necessary to know whether resources are depleted by usage or whether they recover to a sufficient extent during usage. Important to resource availability is the competition among different utilisations. This means that situations are possible in which the same resource can be applied only by one party and is blocked for employment by others. Relevant resources that are not depleted by utilisation, but are characterised by competing applications, are available surface area and space. Using an area for

2.2

Indicators for the Evaluation of Balancing Strategies

15

building up a new power plant, for example, fixes the respective land use for the lifetime of the plant. Another example is energy crops competing with the cultivation of food. Indeed, the quality of land could change due to specific usage. In that case, re-establishment to the previous state is in the first instance a question of costs and the loss of values, and not of critical loads. To a large extent, only the change of land use will have a strong influence on the environment, particularly on the entire ecosystem, so that this kind of usage can be interpreted as being critical. An evaluation of land use change should be carried out, as far as possible in comparison to the previous land use. In addition to recovery costs, losses of utility, as well as other (non-use) values (e.g., option value, loss of originality), are particularly important for the evaluation of land use changes if the previous state cannot be recovered. A special case is resources for which the recovery rate is larger than the depletion rate, such as regenerative cultivated biomass, and resources not being depleted by usage over time in any way, such as the continuous flow of sunlight and wind velocities. As long as the ability of regeneration is guaranteed, there are no temporal resource problems from using a resource. Further relevant resources in the area of energy systems are materials obtained from the ground. These are on the one hand energetic resources such as gas, oil and coal and on the other hand minerals that are required for the production of energy technologies. These materials are also called non-renewable resources, because their regeneration rate is much lower than the depletion rate. Non-renewable usage of land also has to be mentioned in this context. For these kinds of resources, critical situations may occur that are characterised by increasing shortage and, thus, increasing prices and supply costs. In this way, the amount of known resources being economically exploitable, also called “reserves”, may decrease over time. An important indicator for the resource availability is the ratio of the reserves to the current production (reserves-to-production ratio). This indicates how long the reserves would last if the current production rate was kept constant. Steger et al. (2005, p. 54) also call this indicator the “period of secure practice”. Following Steger et al. (2005), for a sustainable management of non-renewable resources, the “period of secure practice” should not decrease over time and not become less than 60 years. This is the time period estimated to be necessary for restructuring the energy system. Claiming that the reserves-to-production ratio should not decrease does not mean that the respective non-renewable resource must not be used, but that a decrease in the stock of economically exploitable resources must be balanced by reducing the production, e.g., by using alternatives. Scarcity of non-renewable resources can additionally be forced by the monopolistic structure of the supply side, which results from the naturally determined hotspots of resource availability in only a few countries and the large infrastructure required to deliver some of the resources to the demand side, such as pipelines and refineries. Therefore, observable concentration in reserves and delivery and supply chain in nations or companies are further interesting indicators.

16

2.2.3

2 Future Perspectives of Electrical Energy Supply

Indicators for the Design of the Energy Supply System

Following Steger et al. (2002, 2005), three relevant aspects can be distinguished concerning the design of an energy system: supply reliability, risk avoidance and openness of options. Furthermore, the invested and variable economic costs of the options and, thus, the amount of fixed monetary capital, are important. Numerous indicators have been discussed in this area. These indicators aim mostly at the evaluation of complete energy systems (see, for example, Kopfm€uller et al. 2000; IAEA 2005; IEA 2007; RNE 2007). However, in this study the subject of investigation is only a part of the energy system. Thus, only some of the discussed indicators are applicable to this analysis. Concerning supply reliability, it is important that the quality of electricity supply with a high share of renewable energy sources, such as solar radiation and wind, can be ensured sufficiently through balancing electric power and energy. Strategies and technologies applicable for this purpose are at the focus of this study. A sufficient quality of supply would of course be reached if the quality provided were the same as that of the current energy system. Additionally, it has to be discussed in how far flexibilities on the demand side should be considered in the system in order also to use demand-side management and to outbid the allowed ranges in which no increase of damages to devices and to people is anticipated. A further aspect that is relevant for supply reliability is the extent to which dependencies on third parties exist with regard to purchased resources. This issue has also been discussed in the previous section. With respect to the aim of risk avoidance, risks that are not acceptable to society should be obviated and high risks should be minimised as far as possible. Beyond technical risks, risks related to environmental burdens are considered here. This includes risks with a large number of small potential individual impacts, including on human health, for which impacts should be minimised. In addition, large-scale risks are also relevant; these are, for example, major environmental damages. Avoiding such risks requires the establishment of critical limits as defined by society. Maintaining an openness of options for new discoveries stemming from research and development is important for realising an optimal energy system. Different energy technologies show various levels of potential promise in this regard. Interesting characteristics of the technologies are the applicability of alternative fuels, their lifetime and the long-term nature of required investments. Investment costs and variable costs of the different technological options are major variables to take into consideration in the design of a future energy system. Once a decision is made for a specific option, costs occur, binding up capital that could otherwise be invested in alternative societal aims. Thus, it is important to look closely at costs. However, to get the whole picture, socio-economic costs have to be taken into account, additional to microeconomic components. Furthermore, long time periods have to be taken into account, because low costs at present may implicate high costs in the future. In the approach followed for this study, energy system set-ups will be optimised for certain points in time, while the framework

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17

conditions and political decisions influencing the implementation of strategies will be considered. The starting points for the projection of framework conditions are future scenarios derived within other studies (see Sect. 3.1). Additional to already existing studies, this study will analyse strategies for balancing power and energy for electricity supply in greater detail than has been done previously and will likewise also consider economic, political and legal aspects.

2.3

Political Governance Towards a Renewable Energy Electricity System in Europe

The theoretical discussion above relating to the aims and goals for a viable, lowcarbon future energy supply is important as background information. It is society, however, that must decide on the necessity of investing in and developing a new energy system (or in this case, electricity system), the direction of that system, and the extent of measures to be taken to spur on the transition. To get a picture of actual developments with respect to the establishment of a new electricity system, a detailed analysis of current and planned political governance processes and policies is indispensible. The analysis starts with a description of the system and the current trends reflecting the impacts of already initiated policies. This is followed by a discussion of specific policy activities that are aimed at restructuring the electricity system. Finally, important challenges for energy policy are discussed.

2.3.1

Historical Background, Current Status and Development of Europe’s Energy System

A variety of factors are driving a slow transition of European approaches to energy in general, and electricity in particular, including concerns about Europe’s heavy dependence on energy imports from abroad, rising fossil fuel energy prices, and ecological constraints. These concerns were summed up in a January 2007 European Commission Communication on EU energy policy: “[T]he days of cheap energy for Europe seem to be over. The challenges of climate change, increasing import dependence and higher energy prices are faced by all EU members” (European Commission 2007a). The challenge for Europe is providing the right incentives and structures to make an energy transition towards greater renewable energies, especially in the electricity sector, possible. The transformation will require not only technological innovations and engineering solutions, but also an appropriate policy framework and public understanding and acceptance.

2.3.1.1 Europe’s Growing Energy Dependence In 2009, close to two-thirds of the total energy consumption mix in Europe was based on fossil fuels (36.6% oil, 15.7% coal, and 24.5% natural gas). Nuclear held a 13.6% share and renewable energies combined an 8.9% share (Eurostat 2011d).

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2 Future Perspectives of Electrical Energy Supply

However, European supplies of fossil fuels are constrained. The European Union is a net energy importer. Its dependency on energy imports has increased from 45% in 1997 to 53.8% in 2008. EU energy dependency is particularly high in the cases of oil (83.5% in 2009), coal (62.2%) and natural gas (64.2%) (Eurostat 2011d). With growing demand for energy resources and minerals coming from emerging economies (e.g., China, India, South Africa, Brazil), expectations are that energy prices will rise, hurting European economies.

2.3.1.2 Climate Change Constraints Even more pressing than these resource constraints are the environmental constraints tied to the heavily fossil-fuel based economies of Europe and other regions of the globe. The Intergovernmental Panel on Climate Change (IPCC) and many other bodies warn that the emissions from fossil fuel burning are contributing to a warming of global average temperatures and putting the planet at risk of severe weather extremes. The warming of the planet will affect seasonal temperatures and rainfall patterns, turning some parts of the planet into desert-like regions and others into flood areas. The melting of polar ice and glaciers could contribute to sea level rise, impacting coastlines and low-lying states. More severe storms and hurricanes and periods of excessive heat and drought are also predicted. The survival of planet and animal species could also be put at risk (IPCC 2007). 2.3.1.3 Climate Change as a Driving Force Behind the Search for a Low-Carbon Electricity System Climate change policies have been critical to recent changes in European energy policies. Reducing greenhouse gas emissions will require Europe to shift away from its still heavy dependence on fossil energies. Climate change prerogatives, defined to protect from unacceptable climate change effects, have been a driving factor in the promotion of greater energy efficiency, greenhouse gas emission reductions and renewable energy. 2.3.1.4 Growing Diversification of the Energy Supply The incentive to diversify energy supplies and increase domestic production sources is becoming increasingly strong. EU domestic energy production in 2009 stood at 28.4% nuclear, 20.4% coal, 18.8% natural gas, 12.8% crude oil, and 18.3% renewable energy. It is striking that by far the fastest growing energy sector is renewables, which accounted for only 9.7% of domestic energy production in 1999, but, as noted above, twice that amount a decade later. Based on Eurostat data, it is possible to calculate that during the same time frame production of other energy sources fell: crude oil (
33%), natural gas (
14.5%), and solid fuels (
14%) (Eurostat 2011d). Thus, the incentive to diversify energy supplies and increase domestic production, especially of renewable energy, is becoming stronger. Renewable energy power capacity is expanding. The EU has begun to think more strategically about how it can shift from its still heavily fossil-fuel based energy structure toward a more low-carbon energy supply. While Europe remains heavily dependent upon fossil fuels, a clear shift in the

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energy mix over time is becoming visible. In the electricity sector, renewables accounted for 11.9% of EU-27 gross electricity consumption in 1990, 13.8% in 2000, and 16.7% in 2008 (ibid.). As renewable energies are relatively noncontroversial, can be domestically developed, and are also climate-friendly, there has been a big push in this direction in recent years. The challenge for the coming decades will be to create an infrastructure, including electricity grid structures and storage systems, that will make possible the further rapid expansion of renewable energy.

2.3.1.5 Trends in Renewable Energy Production in Europe There was a 38.4% increase in renewable energy production capacity between 2002 and 2007 within the EU. During the same time frame, domestic production of other energy sources dropped off: 28.7% in the case of crude oil, 18.1% in the case of natural gas, and 11.1% in the case of solid fuels. Renewable energy growth in electricity generation has been particularly strong in relation to photovoltaics and wind (see Fig. 2.1).

2.3.2

Political Governance Activities for Organising the Future Energy System

2.3.2.1 Regional Cooperation in Developing Renewables There are several ambitious regional renewable energy policies that are forming. One is in the North Sea region, where Norway, Sweden, Germany, France, the Netherlands, Denmark and the United Kingdom are cooperating in the development of a regional grid structure and offshore wind parks. For northern Europe, offshore wind could provide large shares of electricity in the future years, although this will require the development of a grid structure to transport the wind from offshore wind 45,000 40,000

[1,000 toe]

35,000 30,000 25,000 20,000 15,000

solar PV wind geothermal hydro

10,000 5,000 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Fig. 2.1 Electricity generation from renewable sources (Data source: Eurostat 2011g)

20

2 Future Perspectives of Electrical Energy Supply

park locations to demand centres. The German Environment Advisory Council (SRU) has focused attention on the important potential of offshore wind in the North Sea and pump storage capacity in Scandinavia for contributing to meeting ambitious renewable energy goals (SRU 2011). Interest in the large-scale solar energy potential of the Mediterranean and northern African regions are also rapidly building in Europe. The German Aerospace Center (Deutsches Zentrum f€ ur Luft- und Raumfahrt – DLR) has conducted satellite-based studies that suggest as little as 0.3% of the desert areas of the Mediterranean and northern Africa would be necessary to produce enough electricity and desalinated seawater to meet the expanding needs for energy and water in Africa and Europe. Before solar energy could be delivered to Europe from the region, grid interconnectivity will have to be achieved. Efforts to integrate energy markets in general are still at a nascent stage, but movements are rapid. At the bilateral level, Joint Declarations on Energy Cooperation have been signed between the European Commission and Morocco (July 2007) and Jordan (October 2007) and an EUEgypt Memorandum of Understanding on Energy was reached in December 2008 (European Commission 2008a). At the multilateral level, plans are forming for a Mediterranean Ring under the European-Mediterranean Partnership (the Barcelona Process). The idea is to provide electric power transmission grid interconnectivity among the littoral states of the Mediterranean Sea. The concept envisions linking electric power grids from Spain to Morocco, on to the Magreb (north Africa and western Arab) countries, through Egypt and the Mashreq (eastern Arab) countries, and on to Turkey and then Greece. The electric grid could potentially link into the European grid through Greece. Currently, the integration of electricity markets is still limited. The European Commission is helping to fund related projects, such as the Maghreb Electricity Sub-Regional Project, which aims to create an electricity market among Morocco, Tunisia and Algeria. Morocco and Algeria are cooperating in a joint venture to connect the Algerian power grid to the European Union through Morocco. The initial objective of the Mediterranean Solar Plan is for 20 GW of added renewable energy capacities by 2020 for the region. It is expected that 3–4 GW of this will come from photovoltaics, 5–6 GW from wind and 10–12 GW by concentrating solar power (CSP). CSP uses mirrors that reflect and concentrate sunlight on a central column filled with water, in turn turning the water into steam that can be used to drive turbines. For this plan to function, the physical interconnection of Tunisia and Italy and Turkey and Greece is considered necessary (EPIA 2008). The TREC international network of scientists and engineers (now known as the DESERTEC Foundation) together with the Club of Rome have presented an idea for solar energy development in the deserts of northern Africa: DESERTEC, Clean Power for Europe. DESERTEC envisions a future where mass-scale production of concentrating solar power (CSP) in the deserts of northern Africa will supplement European renewable energy sources and help Europe to reduce its carbon dioxide emissions and meet its electricity needs.

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A group of 20 German firms, including Siemens, Deutsche Bank, RWE and E.on plan to form a consortium to invest in the order of 400 billion € into the development of CSP in northern Africa. The goal will be to achieve 15% of European electricity needs within a decade (Connolly 2009).

2.3.2.2 National Actions Within the EU on Climate Change and Renewable Energy There is considerable diversity in both renewable energy supply and renewable energy policy among the member states of the EU. Iceland and Norway have already achieved 100% renewable energy for their electricity consumption. (Norway at times even produces more renewables than it can consume.) Due to the early introduction of a favourable feed-in tariff, Denmark expanded the share of renewable energy in its gross electricity consumption from 2.6% in 1990 to 28.7% in 2008. In the same time period, Germany, which also introduced a feed-in tariff, expanded the share of renewable energies from 3.8% to 15.4%, Ireland basically more than doubled its share from 4.8% to 11.7%, the Netherlands increased from 1.4% to 8.9% and Spain saw a growth from 17.2% to 20.6% share. Some countries, however, saw little change in the share of their renewables in their gross electricity consumption (e.g., Italy) or even experienced a decline. In Austria, there was a drop from 65.4% to 62% and France from 14.8% to 14.4% (Table 2.1). Efforts to develop a EU renewable energy-based electricity structure will be heavily influenced by the block’s three largest economies: Germany, the United Kingdom and France. All three have in recent years shown signs of more strongly embracing renewable energy, although big differences remain among them, particularly in their positions on nuclear energy. France is a relatively small emitter of greenhouse gases, largely due to its heavy dependence on nuclear energy (78% of electricity) and hydroelectric plants (12%). In 2007, the French government launched the Grenelle de l’Environnement, under which it plans to invest in fourth generation nuclear power plants, develop renewable energies, and promote public transportation and green buildings. The United Kingdom is the EU’s largest producer of oil and natural gas. North Sea oil and gas production peaked in 2000, however, and since then the United Kingdom has become a net importer, although its import dependency (21.6% in 2006) is relatively low compared with, for example, Germany (62%) or the EU average (54%). The United Kingdom could also be strongly impacted by climatic changes should sea levels rise or the Gulf Stream shift course. The British parliament became the first in the world to set a long-term, legally binding framework to address climate change when it passed the Climate Change Act in 2008. The Act mandates a cut in greenhouse gas emissions by 80% by 2050. The law requires that the UK’s carbon account be 80% below 1990 levels by 2050; moreover, it requires a reduction of at least 26% by 2020 (compared with 1990) and periodic carbon budget reviews (Turner 2008). The British strategy for meeting this goal includes plans for renewables, energy efficiency improvements, carbon capture and storage (CCS) and new nuclear power plants (Committee on Climate Change 2009).

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2 Future Perspectives of Electrical Energy Supply

Table 2.1 Share of renewable electricity in gross electricity consumption (in percent) 1990–2008 (Source: Eurostat 2011b) 1990 1995 2000 2005 2008 EU27 11.9 13 13.8 14 16.7 Belgium 1.1 1.2 1.5 2.8 5.3 Bulgaria 4.1 4.2 7.4 11.8 7.4 Czech Republic 1.9 3.9 3.6 4.5 5.2 Denmark 2.6 5.9 16.7 28.3 28.7 Germany 3.8 5.0 6.5 10.5 15.4 Estonia 0 0.1 0.3 1.1 2.0 Ireland 4.8 4.1 4.9 6.7 11.7 Greece 5.0 8.4 7.7 10.0 8.3 Spain 17.2 14.3 15.7 15.0 20.6 France 14.8 17.8 15.1 11.3 14.4 Italy 13.9 14.9 16.0 14.1 16.6 Cyprus 0 0 0 0 0.3 Latvia 43.9 47.1 47.7 48.4 41.2 Lithuania 2.5 3.3 3.4 3.9 4.6 Luxembourg 2.0 2.3 2.9 3.3 4.1 Hungary 0.5 0.7 0.7 4.6 5.6 Malta 0 0 0 0 0 Netherlands 1.4 2.1 3.9 7.5 8.9 Austria 65.4 70.6 72.4 58.4 62.0 Poland 1.4 1.6 1.7 2.9 4.2 Portugal 34.5 27.5 29.4 16.0 26.9 Romania 23.0 28 28.8 35.8 28.4 Slovenia 25.8 29.5 31.7 24.2 29.1 Slovakia 6.4 17.9 16.9 16.7 15.5 Finland 24.4 27 28.5 26.9 31.0 Sweden 51.4 48.2 55.4 54.3 55.5 United Kingdom 1.7 2.0 2.7 4.3 5.6 Iceland 99.9 99.8 99.9 99.9 – Norway 114.6 104.6 112.2 108.4 109.4

Germany has particularly ambitious climate and renewable energy goals and legislation. The German government has actively promoted renewable energy, beginning with the 1990 Electricity Feed-in Law and the Renewable Energy Law of 2000 (with a target for doubling the share of renewable energy in the electricity market from 5% to 10% by 2010). The growth of renewables is also linked to decisions to phase out nuclear energy in Germany. In 2000, the German government passed a nuclear phase-out law (a ban on new plants and a phased shutdown of existing reactors) that targeted a phase out by around 2021. In December 2007, the government introduced an Integrated Energy and Climate Package setting a target of reducing greenhouse gas emissions by around 40% of 1990 levels by 2020. The package included 14 pieces of legislation that promote

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23

energy efficiency and renewable energies in the electricity and heat sectors, among other areas (BMU 2007). Then, in October 2010, the German parliament passed a new Energy Concept for the Future (BMU 2010). The plan reaffirmed an earlier goal of reducing greenhouse gas emissions by 40% by 2020 and also included a series of targets for the coming decades: 55% reduction by 2030, 70% by 2040, and 80–95% by 2050. Renewable energy is to account for 80% of electricity by 2050 (with interim goals of 35% by 2020, 50% by 2030, and 65% by 2040). The share of renewable energies in gross final consumption is also to increase to 18% by 2020, 30% by 2030, 45% by 2040, and 60% by 2050. Energy efficiency is also to be pushed forward, by cutting primary energy use by 50% by 2050 relative to 2008 levels. More controversially, the concept prolonged the shutdown dates of the country’s nuclear power plants by an average of 12 years (Bundesregierung 2010). After the Fukushima nuclear reactor disasters, this decision was again changed. The seven oldest nuclear power plants were taken off line immediately after the Fukushima nuclear catastrophe. They are to remain off line. Another plant that was already off line for technical repairs is to remain off line. This shutdown reduces German nuclear capacity by about 40%. Of the remaining nine plants, six are to be phased out by 2021 at the latest. For the three youngest plants, a 2022 shutdown date is possible. These policy decisions have major implications for energy and electricity policy in the years to come. To meet both its climate change goal and the replacement of nuclear generation capacity, Germany plans to invest strongly in renewable energy development. This means there will need to be rapid development in centralised offshore and onshore wind, decentralised solar photovoltaics, solar thermal, concentrated solar thermal (in southern Germany, but also possibly in southern Europe and northern Africa), geothermal and biomass. It will also be necessary to develop electricity storage capacity and build a high-voltage grid structure. As can be seen, the three largest economies of the European Union have very different energy mixes. This complicates efforts to establish common goals on electricity generation across Europe. Nevertheless, the EU has managed to win consensus on promoting the growth of renewable electricity. Due to geographic as well as political and economic factors, the extent and distribution of renewables in the final total energy mix of member states varies substantially. Countries where there is large hydro potential – Norway, Sweden, Finland, Austria and Switzerland – can meet large shares of domestic demand from hydro. They may also in the future be able to provide hydro-pump storage capacity. Denmark, Germany and Spain have done comparatively well in building non-hydro renewable energies (wind and, in the case of Germany and Spain, also substantial amounts of solar). Denmark obtains approximately one-quarter of its electricity from wind. Germany has experienced a strong growth in renewables in the past years, so that between 2005 and 2010, the share of renewables grew more than 10% to approximately 17% of the total final electricity consumption. Along with further expansion of renewable energy at the national level, for Europe to achieve a greater share of its electricity from renewables in the future will require far greater cooperation among member states, better interconnectivity, and the development of high-voltage electric grids and electricity storage infrastructure.

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2 Future Perspectives of Electrical Energy Supply

2.3.2.3 European Policies for a Low-Carbon Energy Market In comparison with the level of policy harmonisation that has been achieved in the environmental area, integration of European energy markets and harmonisation of European energy policy has been relatively limited. Integration and policy harmonisation have been stymied by the different energy mixes of member states and strong concerns about national energy sovereignty. Yet, pressures to change this and to develop a more coordinated and low-carbon energy mix are growing. Despite the strong role of national governments in energy policy matters, considerable progress has been achieved in developing EU targets in areas where energy policy is closely tied to climate considerations. EU climate policy is seen as a way of moving member economies towards greater energy autonomy, resource efficiency and technological progress. Early steps were taken to promote an energy transition in the 1990s when several individual European countries established voluntary greenhouse gas emission reduction targets. Negotiations leading to the formation of the Kyoto Protocol in 1997 further helped to raise European public awareness of climate change. The Kyoto Protocol entered into force in 2005. Under the Kyoto Protocol, the EU-15 committed itself to an 8% cut in their greenhouse gases relative to 1990 levels. Under an internal burden-sharing arrangement, different national targets were formulated for the different member states. The national targets were based on a mix of factors that included national capabilities, the existing energy mix, and per capita economic wealth. Some countries took on very large reduction targets relative to their 1990 emissions levels (Austria
13%, Belgium
7.5%, Denmark
21%, Germany
21%, Italy
6.5%, Luxembourg
28%, Netherlands
6%, United Kingdom
12.5%), others agreed to stabilise their emissions (France and Finland 0%), while other poorer member states were permitted to increase their emissions (Greece þ25%, Ireland þ13%, Portugal þ27%, Spain þ15%), but at rates lower than what a business-as-usual trajectory would have predicted. Sweden adopted a þ4% target but later adopted national legislation that imposed a
4% target by 2010. Trends to develop renewables in Europe began to take on a supranational flavour in the late 1990s in parallel to these climate policy goals. In 1997, the European Community prepared the “Energy for the Future: Renewable Sources of Energy”, White Paper for a Community Strategy and Action Plan (European Commission 1997). This was the first time that the European Community set a renewable energy goal. The goal established then has yet to be achieved: 12% of total energy consumption from renewables by 2010. (As of 2007, the European Union was meeting 6.7% of its total energy needs from renewables.) In 2001, as the European Community began to gear up for ratification of the Kyoto Protocol and, following the implementation of renewable energy legislation in Germany, Spain and Denmark, more serious attention began to be turned to the potential to develop renewables within the electricity sector in Europe. Directive 2001/77/EC formulated a goal to achieve 21% of the EU’s electricity from renewable energy sources by 2010. Indicative targets were established for each EU member state. As of 2008, 16.7% of the European Union’s final electricity

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Political Governance Towards a Renewable Energy Electricity System in Europe

25

consumption was from renewable sources, still short of the 21% target. As of 2007, Denmark, Germany and Hungary were the only countries that had met their specific targets already (European Commission 2009c). In March 2007, the EU Council set a series of new climate and energy goals and targets that were later embodied in EU Decision No 406/2009/EC (European Commission 2009a). The EU recognised the importance of preventing a rise in global average temperatures of more than 2ºC above pre-industrial levels, the level beyond which the IPCC warns that the consequences of climate change could become particularly severe and possibly irreversible. For developed countries, this meant achieving a reduction of 60–80% of greenhouse gas emissions compared to 1990 levels. To begin the process of meeting this challenge, the EU committed to reducing the EU-27’s greenhouse gas emissions by 20% of 1990 levels by 2020 or 30% if other major emitting countries commit to comparable action, expanding the share of renewable energy in the EU’s primary energy mix to 20% by 2020 and enhancing energy efficiency by 20% compared to 2005 levels by 2020. These goals are to be reached with the assistance of various policies and programs. One is a revision of the EU carbon Emissions Trading Scheme (ETS) that was established by Directive 2003/87/EC. The EU ETS covers over 12,000 major emissions sources (e.g., utilities, manufacturing industries, cement industry, pulp, paper) and covers approximately 40% of all EU carbon dioxide emissions. As a result of the Linking Directive (Directive 2004/101/EC), emission reduction credits obtained through the clean development mechanism and joint implementation, including in renewable energies, can be used in the ETS (European Commission 2004). The first phase of the emissions trading scheme, which ran from 2005 to 2007, encountered some serious problems due to an over-allocation of permits by individual member states to their industries. As a result of stronger control and intervention by the European Commission, national governments issued fewer permits for the second phase, which runs from 2008 until 2012. The third phase, which begins in 2013, will gradually phase out the free allocation of emission allowances and replace it with auctioning. To meet the 2020 goals, the emission allowances available to industries will be reduced by 21% of 2005 levels by 2020 (European Commission 2010b). Second, much as is the case under the Kyoto agreement, national effort sharing arrangements were introduced to cover emissions from sectors not covered by the ETS: housing, transportation, agriculture and waste. Decision number 406/2009/EC of the European Parliament and of the Commission distributed greenhouse gas emission reduction targets among member states. The reduction targets are relative to 2005 emission levels. Emission reduction targets were influenced by member states’ economic wealth (GDP/capita). Richer states agreed to higher reduction targets. Thus, Luxembourg, Denmark and Ireland must reduce their emissions by 20%; Spain by 17%; Austria, Belgium, Finland, the Netherlands and the United Kingdom by 16%; Germany and France by 14%; Italy by 13%, Spain by 10%, Cyprus by 5%, and Greece by 4%. Other states will be allowed to increase their emissions, but at a rate below business-as-usual estimates. Thus, Romania and

26

2 Future Perspectives of Electrical Energy Supply

Bulgaria, for example, are allowed to increase their emissions, respectively by 19% and 20%. Poland is permitted a 14% increase and Hungary a 10% increase. The combined impact of these targets is expected to reduce EU emissions in sectors not covered by the ETS by 10% of 2005 levels by 2020. States will be permitted to use the Kyoto flexibility mechanisms to meet some of their reduction targets. The combined emission reduction cuts through the ETS and non-ETS sectors are expected to result in total reductions in greenhouse gas emissions by 20% of 1990 levels by 2020 (European Commission 2009a). Third, in January 2008, the European Commission issued a draft directive that called for an increase in the share of renewables in final energy consumption from the 8.5% level achieved as of 2005 to 20% by 2020. The European Parliament approved Directive 2009/28/EC (the Renewable Energy Directive) in December 2008. All member states are obliged to expand their share of renewables by a minimum of 5% from their 2005 levels. In addition, depending on a country’s per capita GDP and renewable energy conditions, additional amounts were taken on by some countries. To apply pressure on member states to fulfil their goals, interim targets were set up as well. States are expected on average to have met 25% of their goal between 2011 and 2012; 35% between 2013 and 2014, 45% between 2015 and 2016, and 65% between 2017 and 2018. A similar kind of burden-sharing agreement to that used with the Kyoto Protocol was established to meet the EU’s 20% renewable energy target. Member states’ targets were determined on the basis of a formula that included a flat rate increase in renewables of 5.5% above their 2005 levels and an additional increase based on per capita gross domestic product (European Commission 2009b). Ten states have renewable energy targets ranging from 10% to 15%, eleven states targets from 16% to 25%, and six states targets of 30–49% (ibid.:46) (Table 2.2). Within the different member states of the EU, there is a wide variety of different support schemes in operation, including feed-in tariffs, premium systems, green certificates, tax exemptions, requirements for fuel suppliers, public procurement expectations, and research and development programs. Largely due to sovereignty concerns, the Commission has concluded that while harmonisation of support schemes may be desirable in the long run, at the present time, cooperation between countries and optimisation of existing support schemes must be pursued (European Commission 2005b, 2008c). The Commission has also called for pursuing means to promote long-term stability for investors. Importantly, there is a link between the Renewable Energy Directive and market trading. Under the directive, member states can link their national support schemes to those of other EU member states. In addition, the directive allows for the import of “physical” renewable energy from third-country sources (making it possible, for example, to import renewables from North Africa). Open trading in renewables is restricted to trades of excess renewables credits (in the form of “statistical transfers”) among member states that have met their interim targets (EurActiv 2011a). A fourth element is a directive addressing the legal framework for carbon capture and storage, a technology that is still in the early stages of development.

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Political Governance Towards a Renewable Energy Electricity System in Europe

27

Table 2.2 Burden sharing: national renewable energy targets for 2020 (flat rate increase in renewables of 5.5% above existing levels & additional increase based on per capita GDP) Member state Share of renewables 2005 (%) Share required by 2020 (%) Austria 23.3 34 Belgium 2.2 13 Bulgaria 9.4 16 Cyprus 2.9 13 Czech Republic 6.1 13 Denmark 17.0 30 Estonia 18.0 25 Finland 28.5 38 France 10.3 23 Germany 5.8 18 Greece 6.9 18 Hungary 4.3 13 Ireland 3.1 16 Italy 5.2 17 Latvia 32.6 40 Lithuania 15.0 23 Luxembourg 0.9 11 Malta 0.0 10 The Netherlands 2.4 14 Poland 7.2 15 Portugal 20.5 31 Romania 17.8 24 Slovak Republic 6.7 14 Slovenia 16.0 25 Spain 8.7 20 Sweden 39.8 49 United Kingdom 1.3 15

Many other related directives exist as well. Examples include Directive 2006/32/ EC on energy end-use efficiency and energy services, passed in April 2006. This directive establishes a target of a 9% cut in energy use over business-as-usual trends between 2008 and 2017 and requires a rolling series of energy efficiency action plans (2007, 2011, 2014) (European Commission 2006, p.73). Directive 2010/31/ EU, passed in May 2010, on the energy performance of buildings complements Directive 2009/125/EC of the European Parliament and of the Council of 21 October 2009 establishing a framework for the setting of ecodesign requirements for energy-related products and Directive 2010/30/EU of the European Parliament and of the Council of 19 May 2010 on the indication by labelling and standard product information of the consumption of energy and other resources by energyrelated products.

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2 Future Perspectives of Electrical Energy Supply

2.3.2.4 The European Energy Council of 2011 The 2011 European Council (4 February 2011) meeting focused special attention on the importance of securing for Europe “[s]afe, secure, sustainable and affordable energy contributing to European competitiveness” and called for “a fully functioning, interconnected and integrated internal energy market” by 2014. The goal is to allow gas and electricity to move freely across the EU. The Council called upon ACER national regulators and transmission systems operators to move forward on market coupling and guidelines as well as on network codes applicable across European networks. The Council also concluded the importance of adopting technical standards for electric vehicle charging systems by mid-2011 and for smart grids and meters by late 2012. The Council decision also focused attention on the need to interconnect networks across borders in order to “ensure that solidarity between member states will become operational, that alternative supply/transit routes and sources of energy will materialise and that renewables will develop and compete with traditional sources.” The Council suggested that this requires streamlining and improving authorisation procedures for the building of new infrastructure. The Council further called for greater investments in energy efficiency to enhance competitiveness and strengthen security of supply and to put the 20% energy efficiency target for 2020 on track (European Council 2011). 2.3.2.5 Moving Towards Higher Emission Reduction Targets There are growing discussions as to whether the EU should move beyond its 20% target for 2020. In 2010, the Commission released a Communique´ discussing the steps that would be necessary for the EU if it were to determine to pursue a 30% emission reduction by 2020 relative to 1990 levels. This has yet, however, to win EU-wide endorsement. Long-term goals are solidifying around a low-carbon energy future for Europe. In October 2009, and again in February 2011 at the EU Energy Summit, European leaders announced a commitment to an 80–95% emission reduction target for 2050 relative to 1990 emission levels. 2.3.2.6 Roadmap for a Low-Carbon Economy in 2050 Success in further expanding the share of renewables in the electricity sector will be dependent upon technological advancements and market signals, political guidance and intervention, and public support. The European Commission has prepared a roadmap for how a low-carbon economy could be achieved by 2050. It should be noted that this is not a legally binding document. The roadmap includes a target of achieving 93–99% CO2 reduction in the electricity sector by 2050 in order to make it possible to achieve 80–95% CO2 reduction in the overall primary energy balance. Mid-term targets for reductions of CO2 in the primary energy mix are 25% reduction by 2020, 40% by 2030, 60% by 2040, and 80–95% by 2050. Pressures are building for Europe to go beyond the 20% greenhouse gas emission reduction target that was established for 2020, although resistance to stronger targets also remains strong. The 25% target

2.3

Political Governance Towards a Renewable Energy Electricity System in Europe

29

appears to be a compromise between the existing 20% reduction target and the proposed 30% reduction target. The roadmap calls for major and sustained investment in renewable energy and smart grids along with carbon capture and storage. It also envisions an electrification of the transport sector. Interestingly, the roadmap, which has been prepared by the Director General for Climate Change, predicts that the transition will require an addition 270 billion € (or 1.5% of EU GDP per annum) on top of the existing 19% of GDP currently spent, but that over a 40-year time frame, energy savings and renewable energies could result in sharp reductions in EU average fuel costs, leading to savings that could amount to between 175 and 320 billion € per year (EurActiv 2011b). With the release of the roadmap, the EU will need to give more attention to the appropriate policy measures and instruments to make the development of a single European electricity market possible. This will require the formulation of national support systems that are flanked by strong EU targets and measures.

2.3.2.7 Supporting Infrastructure Development for Renewable Energy Continued growth in renewable energy capacity will require the development of new electricity grids that are capable of transmitting fluctuating supplies across long distances. Currently, the EU lacks the interconnectors that would make it possible to move electricity across the continent. In November 2010, the European Commission released “Infrastructure priorities for 2020 and beyond – a blueprint for an integrated European energy network” (European Commission 2010a). As the blueprint notes, already the lack of adequate interconnectivity and storage capacity has prevented the EU from being able to respond to energy shortages in some member states or to efficiently make use of existing capacity. Building the necessary infrastructure will require huge investments. The blueprint estimates that around one trillion € will need to be invested through 2020 to meet Europe’s energy system needs. About half of this will be necessary for networks for electricity and gas distribution, transmission, storage and smart grids (ibid.). 2.3.2.8 Public Acceptance An energy transformation could bring many benefits for Europe in terms of reduced health costs and environmental damage as well as in terms of creating new markets and jobs. The renewable energy sector is becoming a major employer in Europe. Europe has become a global leader in renewable energy technologies. It holds about 60% of the world market share in wind energy technologies (European Commission 2007a). Nonetheless, there will be many public acceptance questions associated with the large-scale expansion of renewables. There will inevitably be problems related to land and accession rights needed for the building of renewable energy facilities as well as supporting infrastructure, including grid structures, interconnectors and storage capacity. As has been seen at various times throughout Europe, movements opposing wind parks, solar farms or geothermal facilities have successfully blocked the

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2 Future Perspectives of Electrical Energy Supply

development of some renewable electricity projects and infrastructure. In the future, public acceptance will have to be won if a major redesign of the electricity structure is to be achieved. Participatory decision-making processes must be central to any movements towards wider expansion of renewables. The Ethics Commission for a Safe Energy Supply recommended that the German government establish a Forum for an Energy Dialogue with citizens to involve them in all phases of the planning and decision-making process (Ethik-Kommission 2011). This kind of forum is a matter that should be considered at an early stage of the strengthening of both German and EU renewable energy programs. There are many issues where the public can and should have influence. One area is in relation to the extent to which an approach that is based on larger, more centralised renewable energy facilities and large-scale storage systems or more decentralised structure and storage capacity systems should be followed (e.g., storage systems (batteries) at the household level). Another is in relation to whether grid lines are kept above ground, which is cheaper, or buried, which is more expensive but aesthetically less disruptive. The development of a new electricity structure that incorporates a high percentage of renewable electricity is influenced/affected not only by technological and economic questions but also by societal values and preferences.

2.3.3

Challenges Ahead

Clearly, many challenges remain for a large-scale transformation to a renewable electricity system in Europe. Prior to the Treaty of Lisbon, the European Community had no explicit competence in the energy field. The necessary legal basis for Community action on energy issues stemmed primarily from other policy areas. EU policy on electricity and gas markets was premised on the Community’s competence for forming a common market. Its competence relating to renewable energy was tied to articles on the environment. Changes under the Lisbon Treaty, which came into force on December 1, 2009 and reforms EU institutions and rules, have expanded the rule of the EU in energy policy matters. The treaty has made energy an area of joint competency between the EU and member states. Under the Lisbon Treaty, efforts to further harmonise renewable energy strategies, improve the electricity grid and related storage capacity, promote energy efficiency and enhance energy security should become somewhat easier, although large differences remain in the energy policies, concerns and trajectories of different member states.

2.4

Economics of Storing Values

2.4.1

Energy Economic Background

Thinking about the energy sector usually concentrates on three objectives (Mulder and Willems 2009): (1) security of energy supply, (2) affordability and (3) environmental friendliness. Changes to these objectives or in the potential for their

2.4

Economics of Storing Values

31

realisation can lead to changes in the energy sector. Although the goal of environmental sustainability played only a small role in energy policy decisions in the past, there has been an increase in the public’s consciousness of environmental costs of the existing energy structure. A growing understanding of the link between the burning of fossil fuels and the greenhouse effect has most probably caused this. There is increasingly strong political pressure for the realisation of environmentally sound economic policy. One step in this direction is the European Union’s emission trading system (EU ETS). Another is the CO2 tax introduced in Switzerland and Norway. Clearly, though, not all regions of the world have experienced the same level of concern about climate change. Measures such as those being introduced in Europe are not yet spread widely across the globe. The greenhouse effect is a global environmental problem; this makes it important to consider some basic information about global CO2 emissions. Global greenhouse gas emissions (see Fig. 2.2) have remained stable on a per capita basis for the world population. With growth rates at 2.1% in 1971 and 1.2% in 2002–2008 the growth rate of the world population and of emissions have both fallen continuously. In the OECD countries the population grows only at a rate of 0.6%, but the CO2 emissions per head of the population have had a positive growth rate; growth in emissions falls only during economic crises. In Germany, eastern and western parts together, CO2 emissions have fallen since 1979, not only when measured in per capita terms but also in absolute terms.6 16

Metric tons per capita

14 12

Germany

10 8

High income: OECD

6

World

4 2 0 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Fig. 2.2 CO2 emissions (metric tons per capita) from 1960 to 2005 (Source: World Bank 2009)

6 The reasons for such development are normally discussed in literature addressing the environmental Kuznets curve. This is either panel data analysis or theoretical work. Both approaches are unable to distinguish the difference between Germany and other countries. The major preliminary suspect in regard to Germany is the fall of manufacturing as a share of GDP in the period 1991–1996. The successive numbers are 27.5, 25.9, 23.6, 23.1, 22.6, 22.2. Source: Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, Tennessee, United States (World Bank 2009). Such a sectoral shift cannot be found in any comparable country.

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2 Future Perspectives of Electrical Energy Supply

In addition to energy saving, an increase in energy production from wind and photovoltaic (besides solar thermal, water power, biomass and perhaps7 CCS coal) is necessary. This will increase fluctuations of energy supply, as wind and sun have a huge variability in the electricity amounts they contribute, depending on weather conditions. The larger the regions under consideration and the better the international electricity network, the smaller are the problems associated with fluctuations, as there is a potential to balance different inputs. However, fluctuations never vanish completely. Therefore, it is critical to examine to what extent storage technologies can achieve an intertemporal shift and how large the necessary excess capacity of other technologies such as gas is to overcome temporary shortages. This implies that storage of value enters the area of electricity provision. So far, there has been relatively little storage capacity available. Pumped storage and batteries have been used to a small extent – see the example of Berlin in Sauer (2009) and Chap. 5 of this book – and hydrogen, which can be produced from the use of excess supplies of wind energy and stored in caverns, is still at an early phase of development (Anderson and Leach 2004).

2.4.2

Theory of Storing Values

2.4.2.1 Storing Values Without Technologies Money and Credit If no technology as a store of value were available, value could be transferred into the future by giving something to somebody else against the promise of giving something else back in return later. This would be a non-monetary or real credit. A special form of such a promise is money in the sense of coins and paper (Samuelson 1958). If money is generally accepted and institutionalised, a credit can be turned into goods not only by getting them from the debtor but rather by getting them from any other person. This way, the creditor is not dependent anymore on the promise of a person to deliver goods later against getting other goods now. An example may help to understand the role of money. Without it, the baker could get a pair of shoes from the shoemaker only against the promise of payment through the delivery of a certain amount of bread on each of the following days until a certain point in time. Or vice versa, the shoemaker could get bread for some time against a promise to deliver a pair of shoes later. If, instead, they

7

The literature is very skeptic in regard to the cost effectiveness of CCS. An exception is Golombek et al. (2009) who estimate that CCS will be competitive at a price of $30/tCO2 when integrated but not in its retrofitting versions. At $90/tCO2, coal without CCS would vanish completely according to their calculations. Praetorius and Schumacher (2009) summarise the literature as giving a range of 30–50 €/tCO2 for making CCS (with IGCC) economically viable. The range for capture is 7.6–68.1 €/tCO2, for transport 6–40 € depending on the distance and for storage 1–6 € depending on the type of place. Alphen et al. (2009) however point out that the Norwegian CO2 tax has gone up 40 €/tCO2 without making CCS competitive so far; it is currently announced to be in place in 2015.

2.4

Economics of Storing Values

33

have money in coins or notes, they can pay each other exactly what they owe and the one receiving the money, say the shoemaker, can buy something else from somebody else with the baker’s money, rather than only getting bread from the baker who buys the shoes. In brief, barter trade and promises are replaced by a form of monetary credit that is accepted by everyone and, in this way, serves as a store of value. Land and Heritage Another way of transferring value into the future is through buying things such as land. Land is tied to nature, which can be preserved in its quality and can be transferred into the future by way of a handover to the next generation. Time for Education Still another possibility of transferring value into the future is through investing time into education and using the acquired skills in later periods. Knowledge can be transferred to later generations even without using technologies such as printing books, or having schools. The advantage of institutionalised schools in transferring knowledge is that the recipient gets not only the knowledge but also a certificate testifying that he has acquired the knowledge. Acquiring land, money and education are ways, therefore, of transferring value into the future without necessarily relying on technologies.

2.4.2.2 Storing Values Using Technologies Buildings and Machine Capital Closely related to land are buildings. Buildings are not only useful because we can live in them now, but they will always be needed in the future and, therefore, are a valuable store of value, which is appreciated particularly in inflationary times. Similarly, buying machines allows production for a long time. Capital in the form of buildings and machines is a common way to store value. Printing and Patents Whereas education is partly a personal and informal transfer of knowledge, the technology of printing can help easing the storage of its value and make it independent of persons whose ability to transfer it may lead to mistakes, gaps and forgetting. Printing makes documentation possible and allows for the written form of patents. Therefore, technological descriptions are made and published. By way of printing, they are dissolved from personal knowledge and can be transferred without change into the future, which will determine their valuation in line with the expected use of the patent. Storing Value Through Transport Technologies: Cement, Electricity A special case of technologies that function as a store of value are those where the production, transport and storing of value take place simultaneously. A case in point

34

2 Future Perspectives of Electrical Energy Supply

is cement production during the truck transport. Electricity sometimes is said to not be storable (Brennan 2009). However, this is wrong in the sense that batteries can be loaded (see Anderson and Leach 2004 and Sauer 2009). With current costs, revenues and technical limitations, electricity is not storable in large amounts.

Store of Value for Electricity Indirect forms of storing electricity include the production of hydrogen and pump storage, which is the act of pumping water and storing it in dams at higher levels for use in the form of hydropower at times when electricity production from wind or sun is scarce. It is one of the questions regarding future developments in the electricity sector, whether the costs and revenues will be changed through low spot prices for electricity at times of strong wind and high prices at times of weak wind and sun activity. Salgi et al. (2008, p. 100) state that “. . . electricity prices are highly unlikely to fluctuate enough to allow for the utilisation of the produced hydrogen in stationary applications” and recommend use in the transportation sector. However, their investigation covers only a 2-day demand capacity; our perspective is one of a 12 (between 10 and 20) day capacity requirement at maximum. Moreover, the more critical aspect may be that hydrogen production is perhaps not yet profitable, even if electricity is available at zero cost, because other costs may also be high. However, once gas has to pay for high CO2 emissions, other flexible supplies of electricity, such as compressed air, hydrogen and electricity made from it, may become more competitive and add to pumped storage capacity. This will be especially true when pumped storage capacity is confronted by a lack of sufficient adequate locations. If energy from wind and photovoltaics get a high market share, the supply of electricity can be ensured cheaply without nuclear energy and CCS coal as long as there is sufficient stored electricity to cover periods of low renewable electricity supply8 (Heal 2009a, b). The problem of fluctuations and total inactivity in wind and photovoltaics will differ by region. For the USA, Heal (2009a, b) indicates that when wind is the source of electricity, four times as much capacity is required relative to what is consumed (i.e., for every one unit of wattage consumed four units of capacity are required) because of the fluctuations of the wind. This ratio is quite realistic for Germany as well. For Germany (see Sauer 2009) wind and photovoltaic may produce a supply of zero for about 12 days (in the range of 10–20).9 For Europe, the average value for wind energy fluctuates much less than in Germany. Therefore, we are in need of either:

8 This does not take into account the costs for nuclear risks and problems with CCS. If it is possible for renewables to be more competitive than CCS coal and nuclear energy, these do need not to be taken into account. In less favourable situations though, every aspect and cent may be important. Heal (2009a, b) assumes that gas cannot be used in the base load, although the UK uses 54% of gas, which cannot all be in the demand following load. 9 The other extreme situation is that of shutting down wind energy if the wind blows too strongly. Also, in these situations other sources are required (Sauer 2009).

2.5

Summary and Conclusions

35

A. Investment in transborder transmission, for example, the Super Grid, at the European level to achieve spatial smoothing, which is in accordance with the general idea of integrating regions more strongly, or B. Overcapacity of other generators, such as gas-fired power stations, in order to compensate for lack of supply as currently occurs during situations of peak load demand,10 or C. Storage facilities at the national level (intertemporal smoothing through storage during high electricity production and use during low production periods). For national storage, currently pumped storage and hydrogen inventories are interesting for low-cost smoothing of 12-days supply gaps (see the chapters on these and related technologies). Here a dual use for stabilisation and other purposes should be aimed at in order to make low prices possible. If international networks are improved, as suggested in point A, then storage facilities can also be located abroad.

2.5

Summary and Conclusions

Starting from the basic aims of economic activity of efficient allocation and just distribution, an action rule has been outlined that gives a normative basis for dealing with constraints of and effects on the environment. It is formulated in priorities. The first is to protect the environment from unacceptable damages. The second is to preserve the total value of produced and natural capital. With these restrictions, as a third priority, intertemporal welfare should be maximised. The fourth priority is that just distribution of basics at present should be realised. This fundament is used to characterise indicators that can be applied for the evaluation of strategies for balancing electricity supply and demand with high penetration of fluctuating renewables in the system. Three categories are distinguished for the indicators: protection of the environment, availability of resources, and design of the energy system with respect to society. As noted above, in addition to theoretical considerations, societal norms and priorities must be appreciated. Society must express which damages it considers unacceptable and how far activities should be raised to combat critical effects that may occur due to environmental change caused by human activities. Looking at energy and environmental policies, it is clear that the most prominent example, which is currently seen as most relevant in the area of energy questions, is the anthropogenic influence on climate. From the review carried out above of current developments relating to the German and European electricity and broader energy systems, including present and planned policies and programs, it is clear that the energy system is already changing. A major driving force is the desire to avoid unacceptable states of the environment in the future that could be caused by

10

Gas-fired power stations can also be employed to satisfy base load demand. For example, in the UK gas currently delivers 54% of electricity supply.

36

2 Future Perspectives of Electrical Energy Supply

anthropogenic-induced climate change. There are several key challenges ahead. One is the importance of encouraging the international energy market by strengthening the technical infrastructure, particularly of grids but also storage capacities, for renewable electricity. Second, the competence of Europe in energy questions is rising, but there is still much that needs to be done to strengthen European competencies with regard to a common electricity market. In the absence of a strengthened European voice, it will be necessary to consider what other ways can be pursued to promote a European-wide restructuring of the electricity system. Third, experience with large-scale energy projects, such as wind farms, show that public acceptance, particularly at the local level, has to be won to realise necessary investments into infrastructure. Participatory decision-making processes are thus central to a wider expansion of renewable energy use. The analysis of the economics of storing values reveals three options for storing electricity values. These need to be analysed in cases where the demand and supply in the energy system have to be levelled out. This is likely to occur when there is a high share of electricity produced from wind and solar radiation. The first option is to expand international grid connections, particularly for transborder transmissions. The second is the over-installation of conventional power plants, e.g., natural gas-fired plants, to compensate for lack of supply. The third is to build up energy storage capacities, primarily of electrical energy. Of course, a mixed strategy is also possible.

3

Existing Energy System Studies

The share of renewable energies has been steadily rising and plans are for this expansion to continue into the future (see Chap. 2). The aim of this study is to provide a transdisciplinary analysis of strategies for balancing differences between electricity demand and supply, which can occur as a result of variations in the availability of renewable energy due to the intermittent nature of sources, such as wind and solar radiation. As the share of renewables in the system increases, this could become an increasingly important problem for Germany and Europe. To this aim, this study works with models of potential future energy systems. Usually, future energy scenarios are created that consider currently implemented and planned policy actions to draw pictures of potential future energy systems. The appropriateness of strategies strongly depends on the technologies available for balancing electricity demand and supply as well as the technologies implemented for power production. Thus, the most basic assumptions concern the future technological environment. The development of complete scenarios of the future energy system would be far beyond the scope of this study. Therefore, in a first step, relevant existing studies are scanned for the properties of prospected energy conversion technologies (Sect. 3.1). In a second step, parameters characterising future energy conversion technologies are explicitly composed in order to define a consistent set of assumptions for the technical framework of the study (Sect. 3.2), before the results are summarised and concluded.

3.1

Applicability of Existing Future Energy Scenarios as Framework Conditions for the Analysis of Strategies

In order to analyse existing studies and their results as a basis for deriving input parameters for the analyses in this study (see Sect. 3.2), first, energy system modelling is discussed from a theoretical perspective and a structure for the characterisation of studies is presented. Second, data requirements for the different parts of the study are also formulated. Finally, existing studies are described and B. Droste-Franke et al., Balancing Renewable Electricity, Ethics of Science and Technology Assessment 40, DOI 10.1007/978-3-642-25157-3_3, # Springer-Verlag Berlin Heidelberg 2012

37

38

3

Existing Energy System Studies

characterised with respect to their general characteristics. This section focuses on the applicability of findings from these studies as potential input data for this study.

3.1.1

Energy System Modelling: A Theoretical Perspective

The modelling of systems requires that a distinction be made between the real system that is to be modelled and the model of the system. A model always represents a theoretical reproduction of the real system and is made with certain purposes of analysis in mind (for theory of modelling, see e.g., Grunwald 1999; Schr€oder et al. 2002, p. 319ff). The process of model formulation always requires in a first step to abstract the essential from the negligible or simplifiable objects and interconnections of the system. Furthermore, these elements of the system have to be described in such a way that the system properties that are to be modelled are accessible to relevant instruments of analysis. Beside the scope of the analysis, the detail of the elements can also be configured differently in the relevant dimensions of, for example, time, space, economic sectors and technical options. Following this description, a model of this kind can be drafted as a network of multidimensional elements, which are interconnected via causal links and have defined system boundaries. The short sketch of the model-building process suggests that it is usually not possible to simply apply a model designed for one purpose to another. Such a transfer application requires detailed analysis of a model’s applicability. As an illustrative example, a model designed for the description of dispersion and chemical transformation of pollutants in a forest area cannot be used to derive an ecological map of species or as a tourist map for hiking. Although some details of one model may be usable and relevant for other purposes, it will not reveal all desired details. Nor in most cases, will it give the required information in such a way that it can be used for decisions about actions that need to be taken. Thus, in the cases of chemical dispersion, ecological maps of species and tourist hiking maps, different ‘models’ of the forest areas are required. Even more complex is the picture if the aim is to consider not only individual, but all relevant functions of a system in order to use the model for policy decisions and taking actions. In this context, the consultation of all models describing the system in relevant ways is important. This kind of multiple criteria decision situation is required for energy systems. Respective indicators for the evaluation of energy systems and technologies with regard to their future viability have already been derived from basic societal aims in Sect. 2.2. They give a framework for the normative evaluation with respect to acceptable future energy systems. The fundamental task of an energy system is to provide energy to the consumer when required. Thus, a basic quality of the energy system is the probability with which energy is available for the consumer when it is needed. This quality represents a main part of energy security. However, the energy should be provided economically efficiently, and the system should be usable over a long time period

3.1

Applicability of Existing Future Energy Scenarios as Framework Conditions

39

without unacceptable impacts on the environment and resource availability (see also Sect. 2.1). Thus, basic elements that have to be considered in energy system models are, in the first line, technologies for energy supply and the amount of energy consumption, taking into account their different properties and their interconnections to each other. All energy system models include these elements, although they include the data with various levels of detail. The models of objects/ subjects (e.g., power production facilities, consumers) and their interconnections include descriptive as well as normative statements. This is a basic characteristic of scientific modelling and cannot be avoided. In fact, all scientific theories and even statements about everyday incidents include normative parts. However, descriptive statements based on universal and trans-disciplinary knowledge – following the observations of Janich (2001) – are to be distinguished from explicitly set assumptions which reflect only one possible value in a larger area of potential shapes. While the first set of statements is decided upon by using a certain methodology for the analysis, e.g., economic optimisation, the statements of the second type have to be set explicitly for each analysis. An intrinsic aspect of energy system modelling is the focus on future situations. This is the major reason why many assumptions are required, and high uncertainties, as well as ignorance, appear in some areas of the system. The variety of models and model results originates from various interests and foci. McDowall and Eames (2006) investigated and characterised the bouquet of approaches for models of hydrogen economies. The discussion can easily be applied for overall energy system analyses (see also Martinot et al. 2007). They distinguish the categories of descriptive methodologies: forecasts, exploratory scenarios and technical scenarios as well as normative approaches: visions, backcasts/pathways and roadmaps. In forecasts, futures are predicted based on current trends or expert opinion. In exploratory scenarios, underlying drivers of change are investigated, “often drawing upon tacit knowledge and expertise, to build internally consistent storylines describing a number of possible futures” (McDowall and Eames 2006, p. 1238). Technical scenarios concentrate on the exploration of future technical systems, emphasising “the technical feasibility and implications of different options, rather than explore how different futures might unfold” (ibid.:1238). “Visions are elaborations of a desirable and (more or less) plausible future” (ibid.:1238). They emphasise the benefits rather than pathways. Backcasts and pathways start with a desirable and plausible future, investigating possible pathways to it. Roadmaps start also with a desired future, but describe a sequence of measures designed to reach it. Elements of the other types of methodologies can be used as the basis for the identification of measures. Beside the different approaches to describe possible futures, the characterisation of McDowall and Eames (2006) includes disciplinary aspects of the methodologies used. Main disciplinary contexts and methodologies applied are those of engineering and economic sciences. Taking out the disciplinary aspects, one could distinguish the following relevant approaches for scientific analysis:

40

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Existing Energy System Studies

– Forecasts: deriving one possible future from current knowledge about future developments, – Temporal exploratory scenarios: generating possible futures, starting with setting framework conditions for the main drivers, – Static (comparative) scenarios: analysing scenarios, including different features to a certain point in time or period of time, – Backcasts: analysing the emergence of explicitly defined futures, – Roadmaps: analysing ways to derive at explicitly defined futures. In addition to the type of modelling used to set up temporal connections from the present to the future, studies include temporal resolutions on several levels. The temporal system boundary, the time horizon envisaged, can be chosen differently. The resolution of the temporal phase between present and the future time horizon can also be set at different levels. Temporal resolution within the time period of investigation (e.g., within 1 year) is also an important defining characteristic. The importance of temporal resolutions for the analysis of the energy system is striking because of their influence on energy demand and, especially for renewable energies, also energy supply. These are directly affected by typical social attitudes and the environmental framework conditions such as natural solar and wind cycles. Structures of space, economic market factors and technological options can also vary in models. In each of these dimensions the area of analysis, as well as its resolution, have to be chosen. An adequate characterisation scheme of energy system studies needs to include, beside the key parameters, information about all relevant dimensions of the modelling process. Considering the main model features of energy models discussed above, for the current study the following scheme is derived for the description of energy system studies. Main categories distinguished are basic information showing the circumstances in which the study has been elaborated, model characteristics, and main in- and output data: – Basic information: • study title, year of publication, • institution, • customer, • authors, • aim of the study; – Model characteristics: • general approach, • region and spatial resolution, • period of time and temporal resolution, • technologies and technical resolution, • used models, type of causal interconnections; – In- and output: • individual results, • input data and individual explicitly set assumptions, • model endogenous results and assumptions.

3.1

Applicability of Existing Future Energy Scenarios as Framework Conditions

3.1.2

41

Basic Approaches in Energy System Analysis Followed in This Study and Data Requirements

The technical core of the strategies to be analysed in this study build technologies applicable for levelling electricity demand and supply. The field of technology options in this context is wide and heterogeneous. From the perspective of energy systems, energy storage and energy distribution technologies can be broadly distinguished. These are to a certain extent competing with each other, because more energy storage capacity and power in the system can reduce the required extensions of the electricity grid, while grid extensions allow more exchange of electricity and, thus, reduce the storage capacity and power required. Figure 3.1 gives an impression of the system in focus. Additional to the technologies required for the transformation and transportation of electricity as well as for storing electricity, intelligent control technologies are needed in the system. These technologies do not reflect a large extra hardware effort for balancing electricity once they are developed. They are expected to be freely programmable and designable so that no principle technical restrictions for realising the control features necessary for implementing optimal strategies arise. The analysis of technologies will concentrate on the technical storage and network aspects without analysing the limits and potentials of required control technologies.

Fig. 3.1 Rough model of a current electricity network

42

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Existing Energy System Studies

Two approaches are followed in the analysis of the future energy system in this study. The first is to start out from the current energy system and to assess what is additionally required to implement a certain scenario for electricity supply and demand relative to a future target year. Thus, the starting point for this part of the analysis is a future supply-and-demand-scenario together with today’s electricity network. First, the demand of electrical balancing energy and power and the amount of needed storage capacity are derived from existing energy scenarios. Second, the potential for demand-side management in households is analysed, including the intelligent control of domestic appliances as well as decentralised power production in small plants and loading and providing electricity to the grid with batteries, e.g., in electric cars. Third, restrictions and requirements for the extension of distribution grids in the case of decentralised options and for a transmission network in the case of an increase of wind power from on- and offshore plants are assessed. This is done on the basis of assumed future electricity production. These different individual analyses give a rough picture of how large the potential contributions could be of various technologies to balancing electricity supply and demand for, at maximum, a daily scale. They also describe which measures are preferable for achieving such a balance. Major technologies considered in this part will be the: – management of typical domestic appliances, – load-management for electric cars, – controllable cogeneration with heat storages, together with: – restrictions and extension costs concerning the distribution network, – restrictions and extension costs concerning the transmission network. the spatial focus is on Germany. Electricity is balanced relative to variations of a few hours at maximum. The analysis is based on scenarios that include information about: – supply and demand of electricity subdivided by technology, – the structure of the current network, and – estimates about the amount of respective decentralised facilities that can be applied for balancing electricity flows in the system. The second approach concentrates on the analysis of requirements for storage facilities on different time scales, from several days and even weeks down to 1 h, taking into account energy sources in the whole of Europe and assuming network extensions in competition for an optimal realisation. The electricity supply of renewable sources is calculated from a time series of hourly values of wind and solar radiation with a high geographical resolution. The model is drawn on a green field so that, in principle, no restrictions for cost-optimisation, despite the availability of renewable sources, are considered. In further model adaptations, restrictions concerning different national regulations and energy policies in the European states could be taken into account. The transmission network is modelled as a highvoltage direct current (HVDC) network so that stability issues and the already existing high-voltage alternating current networks need not be taken into account. Lower voltage levels of the network are assumed to hold the required capacity.

3.1

Applicability of Existing Future Energy Scenarios as Framework Conditions

43

The main purpose of the model is to explore the required storage capacity and power and with this, respectively, the type of storage capacities needed, either highpower oriented or high-capacity oriented technologies assuming competition to grid extension. In the second part of the analysis a completely new optimal energy system is constructed for a future year, which is able to cope with a high share of electricity supply from renewable energies. The basis for the calculations will be the power capacity for power production from wind and solar radiation in the system together with meteorological data in an hourly resolution to derive the hourly potential of electricity production. It is realised as a simple optimisation model, which intends to cover the following individual technology options: – onshore and offshore wind, – photovoltaics, – short- and long-term storage systems including, beside others, the options of pumped hydro, hydrogen storage in gas fields, and batteries of electric cars and decentralised photovoltaics, – high-voltage direct current (HVDC) transmission lines. The focus of the second part is on the evaluation of the potentials of different energy storage systems versus network extension in an energy system with a high share of renewable energy technologies. Different time scales are covered: longterm, seasonal and short-term, with a maximum resolution of 1 h. The model covers the whole of Europe and also parts of northern Africa. As input, the characterisation of individual future technologies is required. This requires numerous assumptions be made. In order to be consistent, these are harmonised with other analyses as far as necessary. The major aim of redesigning the energy system is to develop a system that is both stable and low-carbon. The main factors pressing for this kind of structural change are the environmental externalities of the current structure and resource scarcity, which could negatively impact electricity supply if the system is not restructured. Restructuring toward a renewable-energy dominant electricity system could also provide Germany and Europe with greater energy autonomy. In order to assure the system contains the aspects required by modern economies and lifestyles and, especially, security of supply, additional system design aspects have to be considered (see also Sect. 2.2). In the respective analysis, which is described in Sect. 5.7, individual technologies for balancing supply and demand are analysed with respect to their performance in these areas. The indicators that will be followed for this task have been derived in Sect. 2.2. Technologies considered for the analysis of technologies with respect to their impact on resource use and environment are: – upgrade and extension of electricity networks together with over-installation of wind power and photovoltaics, – pumped hydro, – hydrogen storage, – batteries.

44

3

Existing Energy System Studies

As far as possible, the assumptions of all three parts of the analysis introduced above will be held consistent.

3.1.3

Comparison of Relevant Energy System Analyses According to Their General Characteristics

A large number of studies with varying emphases address the modelling of the future energy system, but not all of them are appropriate to consider here. The studies mentioned below have been chosen as they include scenarios which can be applied to derive input data for a detailed analysis of energy storage and other measures to meet the system requirements in situations with highly volatile feed-in of electricity due to power generation from wind and solar radiation. Relevant features of the described scenarios are the percentage of application, the share in fluctuating renewable energies and the way energy technologies are considered in the models. Renewable energies, however, are not an end unto themselves but serve to attain the politically resolved targets pertaining to ambitious greenhouse gas savings. Therefore, the reduction of carbon dioxide is an important criterion. The selected energy system studies are compared in tabular form, based on the characterisation scheme described in Sect. 3.1.1, providing information about basic aspects, model characteristics as well as data affecting in- and output. Table 3.1 depicts the analysis of six selected energy system studies, two of them mainly prepared by the German Aerospace Center (DLR) (“Leitstudie 2008” and “Leitszenario 2009” respectively) (Nitsch 2008; Nitsch and Wenzel 2009), one by the Institute for Energy Economics and the Rational Use of Energy (IER) (K€uster et al. 2007, p. 113ff), and three provided by the Institute of Energy Economics at the University of Cologne (EWI) with the collaboration of the consultancies Prognos AG, Institute of Economic Structures Research (GWS) and the economic-research institute Energy Environment Forecast Analysis (EEFA) (Lindenberger et al. 2008; Schlesinger et al. 2007, 2010). The scenarios of these studies will be further considered in the course of this survey. The recent studies by the DLR and Prognos/ EWI/GWS (numbers 2 and 6) seem to be the most interesting in this case, since they are up to date, comprehensive and feature the highest shares of renewable energies. Additionally, the considered time horizon is in Schlesinger et al. (2010) extended to 2050. However, in this extension to 2050 it can be seen that the methodology also changed from using temporal exploratory scenarios to pathway analyses resulting in a roadmap. Scenarios that deal with a distant future (e.g., 2050), until which time large structural changes are anticipated, draw upon pathway analyses that can generate a roadmap but are not very useful for temporal exploration. The data of the energy system development in the studies are quite comparable with respect to the share of regenerative energies and the CO2 reductions from 2020 to 2050. The new scenarios of EWI present much more ambitious data concerning the CO2 targets than the older scenarios for 2007 and 2008. The “Leitstudie 2009” (Nitsch and Wenzel 2009), together with the so-called target scenarios of

“Target scenario” Update of “Leitszenario 2008”, non-regret strategies for the expansion of RE regarding national and European targets

Roadmap Target-setting and path analysis, updated data

BMU

Nitsch

“Target scenario” Path to achieve goal of climate control, depiction of necessary restructuring of the energy supply

Roadmap

Target-setting and path analysis

Customer

Authors

Aim of the study

General approach

Applicability of Existing Future Energy Scenarios as Framework Conditions (continued)

Database of over 13,000 parameters of Europe’s power plants. PANTA RHEI links data interdependently to give direct and

Comprehensive database of Europe’s power plants with technical-economic parameters and characteristics of new RE: detailed data on potentials and generative costs; other technologies: capacity, building time, lifetime, efficiency, specific

Database REF-TECH: relevant technical and economic parameters of RE-technologies (6–8 variants per type of energy and conversion process) for 2000, 2010, . . ., 2050

Database REF-TECH: relevant technical and economic parameters of RE-technologies (6–8 variants per type of energy and conversion

Considered technologies and technical resolution

Comprehensive database of Europe’s power plants with technical-economic parameters and characteristics of new

2008,2020,2030,..,2050

2005,2010,2015,2020 2005,2010,2020,2030

Germany (Europ. context)

2006, 2008, 2010, 2012, 2015,..,2050

Germany (Europ. context)

2000,2005,2008,2010, 2015,.., 2030,2040,2050

Germany (Europ. context)

Target-setting and path analysis

Roadmap

“Target scenario” Analysis of options to achieve targets given by the customer

Schlesinger, Hofer, Kemmler, Kirchner, Strassburg, Lindenberger, F€ursch, Nagl, Paulus, Richter, Tr€uby, Lutz, Khorusshum, Lehr, Thobe

BMWi

Prognos AG/EWI/ GWS

6. Energieszenarien f€ur ein Energiekonzept der Bundesregierung, 2010

2000,2007,2010,2015,.., 2030,2040,2050

Germany (intern. context)

Temporal explor. scenario Economic optimisation, variation of measures

“Political scenario” Effects of different mixes of political measures

Lindenberger, Bartels, Borggrefe, Bothe, Wissen, Hillebrand, Buttermann, Bleul

BDEW with other federations

EWI/EEFA

5. Energiewirtschaftliches Gesamtkonzept 2030, 2008

Temporal horizon/ resolution

Germany

Temporal explor. scenario Economic optimisation, variation of measures

“Political scenario” Effects of different mixes of political measures

Schlesinger, Hofer, Rits, Lindenberger, Wissen, Bartels

BMWi

Prognos AG/EWI

4. Energieszenarien f€ur den Energiegipfel 2007, 2007

Germany

Target-setting and economic optimisation

Roadmap

“Target scenario” Analysis of options to achieve 80% greenhouse gas reduction

K€uster, Z€urn, Rath-Nagel, Ellersdorfer, Fahl

BASF AG

IER

3. IER Reference Scenarios, 2007

Region

Nitsch, Wenzel

BMU

DLR/IfnE

DLR

Institution

2. Leitszenario 2009, 2009

1. Leitstudie 2008, 2008

Study title, year of publication

Table 3.1 Comparison of characteristics for relevant studies

Basic information

Model characteristics

3.1 45

Model characteristics

E3 (most ambitious variant): Strong promotion of RE and CHP, high levels of expansion, other enhanced conditions for RE, introduction of electric mobility and H2 in traffic, pull-out from nuclear energy, emissions trading: auctioning PEE (preference for RE): minimum share of RE: 2020: 20%, 2030: 30%, 2040: 40%, 2050: 50% for electricity generation, 2050: 45% of total primary energy supply, pullout from nuclear energy, no CCS, GHG reduction targets (to 1990): 2010: 21%, 2020: 35%, 2030: 50%, 2040: 65%, 2050: 80%

Reference scenario (adherence to politics): no explicit climate protection policies

Structure conforms to Leit2008, identical demographic and economic design parameters additionally consideration of developments in the RE-sector and political decisions until mid-2009

Leit2008 (appliance with policy targets): Extrapolation of promotion of RE and CHP, pull-out from nuclear energy, emissions trading: auctioning

Input data/assumptions

investment costs, operation costs, variable costs (without fuels)

3. IER Reference Scenarios, 2007

TIMES-D German part of TIMES (The Integrated MARKAL-EFOM System) developed at IER

2. Leitszenario 2009, 2009

ARES and others (STEP, ARES/KODARES BalanceED) KODARES quantifies the costs by combining the data from ARES with EEG-presettings (rewards, share in costs)

process) for 2000, 2010, . . ., 2050

1. Leitstudie 2008, 2008

Used models, type of causal interconnections

Study title, year of publication

Table 3.1 (continued)

KV (coalitions agreement): Productivity of energy duplicates, extrapolation of promotion of RE, pull-out from nuclear energy, emissions trading: gradual auctioning EE (focus on RE): Strong promotion of RE, learning curves taken from DLR

III (priority environmental protection): Strong promotion of RE and CHP, pull-out from nuclear energy, emissions trading: gradual auctioning

I (adherence to politics): extrapolation of promotion of RE and CHP, pull-out from nuclear energy, emissions trading: free

CEEM, GMES, sectoral macroeconomic structural models

plants incl. learning curves

plants incl. learning curves

CEEM, GMES (optimisation in conversion sector) and sector-specific bottom-up models for demand

5. Energiewirtschaftliches Gesamtkonzept 2030, 2008

4. Energieszenarien f€ur den Energiegipfel 2007, 2007

“Target scenarios” (lifetime extension of nuclear energy): Reduction of GHG: 2020: 40%, 2050: 85%, RE: 2020:
18%, 2050:
50%, extension of nuclear energy: 4/12/ 20/28 years

Reference scenario (adherence to politics): extrapolation of promotion of RE and CHP, pull-out from nuclear energy, rate of RE (gross energy consumption) in 2020: 16

DIME, PANTA RHEI, modular sector-specific bottom-up models

indirect economic effects

6. Energieszenarien f€ur ein Energiekonzept der Bundesregierung, 2010

3

Input and output

46 Existing Energy System Studies

36/53/79

% CO2-emission reduction relative to 1990

42/60/85

–

Learning curves, parameterisation of technologies

18/29/41

Share of fluctuating RE (% of GPP, otherwise stated)

30/50/81

Share of RE (% of GPP, otherwise stated):

% of FPC: 21/34/64

“Leit2008” “E3”

Scenario

Model endogenous results and assumptions

Individual results (2020/2030/2050)

Learning curves, parameterisation of technologies

38/57/80

21/36/44

34/58/84

“Leitszenario 2009”

41/- /-

17/- /-

30/- /-

“EE”

Time frame/time steps of optimisation, learning curves and parameter of technologies, replacement parameters for technologies

35/50/80 39/- /-

Exact definition of technologies, parameterisation of technologies

35/50/80

% of net power production: 11/12/30 13/- /7/9/14

% of net power production: 16/18/24 19/26/53 24/- /-

“Reference” “PEE” “KV”

“III”

40/50/-

35/49/62

22/31/38

34/45/54

42/63/86

23/35/58

35/50/80

“Reference” “Target”

Time frame/time steps of optimisation, learning curves and parameter of technologies, replacement parameters for technologies PANTA RHEI: highly endogenised (apart from world market variables of the GLODYM-System);

Time frame/time steps of optimisation, learning curves and parameter of technologies, replacement parameters for technologies

25/30/-

% of gross power consumption: 15/21/11/15/-

% of gross power consumption: 25/35/ 20/26/ -

“I”

BMU: Bundesministeriums f€ur Umwelt, Naturschutz und Reaktorsicherheit, BMWi: Bundesministeriums f€ ur Wirtschaft und Technologie, BDEW: Bundesverband der Energie- und Wasserwirtschaft, EEG: Erneuerbare Energien Gesetz, RE: renewable energies, CHP: combined heat and power, GPP: gross power production, FPC: final power consumption

Input and output

3.1 Applicability of Existing Future Energy Scenarios as Framework Conditions 47

48

3

Existing Energy System Studies

Schlesinger et al. (2010), show the highest shares of regenerative energies of all scenarios, reaching approximately 58/84% and 50/80% share of renewables of gross power production in the years 2030/2050 respectively. The target scenarios of Schlesinger et al. (2010) depict the most ambitious situation. They reach the highest reductions of CO2 emissions with a certain share of renewable energies. The shares of volatile renewables in 2030 are comparable between the DLR scenario (2009) and the EWI scenario (2010), accounting for 36% and 35% respectively. However, for 2050, Schlesinger et al. (2010) results showed slightly higher shares of fluctuating renewable energies with respect to the gross power production than the “Leitstudie 2009”, namely 58% versus 44%. Generally speaking, the shares of fluctuating renewable energies are rather high and predicted to grow until 2050 in all scenarios. This underlines the importance of compensating strategies. The share of wind and photovoltaics with respect to the installed renewable energies is different in the scenarios of DLR and EWI. The relative value in the “Leitszenario 2009” decreases from 62% in 2030 to 52% in 2050 regarding gross electricity production, whereas in the EWI target scenarios the value rises from 70% to 73%. The scenarios shown here predominantly build the basis for the development of future electricity supply parameters, which serve as input for the subsequent analysis of balancing strategies. Section 3.2 describes how the studies are used to deduce representative scenarios for the future energy system in Germany with diverging emphases of the future fossil power plant structure and the development of renewable energies. The scenarios represent the basic starting point for the analysis of German conditions in Sect. 3.2 and Chap. 4. In the third analysis (Sect. 5.7), the assessment of the future viability of technologies requires data that is at least at the European level, because technology production chains cannot be reduced to the national level. Even end products are not typically produced simply nationally. Unfortunately, available databases in this area are weak. Sufficient life cycle data for future years with a focus on the energy sector in Europe are only available from one source, this being the results of the European integrated project, “New Energy Externalities Development for Sustainability” (NEEDS). The project addresses new methodological developments in the area of external cost estimations, energy economic modelling and life cycle analysis of energy systems for 2025 and 2050. In NEEDS, three future electricity generation scenarios have been described: a “very optimistic”, a “pessimistic” and a “realistic-optimistic” scenario.1 The very optimistic mix assumes an extensive integration of renewable energies in Europe with a share of 80% (see Fig. 3.2). It is based on an ambitious global scenario that

1 “Very optimistic”, as used here, exactly corresponds to the selection “electricity mix UCTE, very optimistic (VO), enhanced renewables (Renew.), 2050”, “realistic-optimistic” to “electricity mix UCTE, realistic-optimistic (RO), 440 ppm, 2050” and “pessimistic” to “electricity mix UCTE, pessimistic (PE), business as usual (BAU), 2050”, correspondingly to ESU, IFEU (2008, p. 49ff).

3.2

The Derivation of Future Electricity Supply Parameters

49

100%

Wave energy

90%

CSP

80%

Photovoltaics

70%

Wind Offshore DK Wind

60%

Hydropower

50%

Biomass

40%

Nuclear

30%

Natural Gas

20%

Oil

10%

Lignite Hardcoal

0%

2025

2050

"pessimistic"

2025

2050

2025

2050

"realistic optimistic" "very optimistic"

Fig. 3.2 Share of the different energy resources in terms of produced electricity assumed in the different scenarios in the NEEDS project (ESU and IFEU 2008)

was designed by Krewitt et al. (2007) to keep Europe within the target of a 2 C global average temperature increase over pre-industrial levels. As the aim here is to analyse a scenario with high penetration of renewable energies in the electricity system, the NEEDS “very optimistic” electricity mix is taken for the analysis. The scenario is comparable with the main scenario in the “Leitstudie” and “Leitszenario” respectively which have been generated by the same group.

3.2

The Derivation of Future Electricity Supply Parameters as Inputs for the Analysis of Balancing Strategies

In this chapter, the expected future development of generation capacities with fluctuating feed-in as well as the development of the conventional power station park for Germany are estimated. As a basis, this involves evaluating the studies on future electrical energy systems that have already been compared above and comparing their core statements. Two different and representative scenarios are created from the determined data, on the basis of which problems for the total electrical power supply system can be derived. The future scenarios derived are based on the established public studies discussed in Sect. 3.1, which are further described in the following. Both assumed political framework conditions (promotion of renewable energy sources, withdrawal from nuclear energy) and assumed economic framework conditions (fuel prices) are crucial influential factors in the

50

3

Existing Energy System Studies

development of the conventional or renewable power station park in the individual scenarios. The present study looks at two scenarios with a political focus, which place different emphases in their characteristics regarding the future development of the power supply. Special attention is paid to the future fossil power station structure and the development of renewable energy sources (RES) in Germany. The scenarios to be examined for energy development in Germany are essentially based on the studies already listed in Table 3.1: – Energy scenarios for the energy summit 2007 (Schlesinger et al. 2007). – Overall economic energy policy concept 2030 (Lindenberger et al. 2008). – Further development of the renewable energy expansion strategy (pilot study 2008) (Nitsch 2008). – Long-term scenarios and strategies for the expansion of renewable energy sources in Germany (lead scenario 2009) (Nitsch and Wenzel 2009). – Energy system development in Germany, Europe, and worldwide – a comprehensive study analysis, 2007 (K€ uster et al. 2007). To determine the installed power of the conventional power stations for the future scenarios, additions and shutdowns are carried out for the different types of power station, based on the present-day database of power stations in Germany (approximately 370 installed power stations), in accordance with the available studies. In addition to the information about the installed power of the individual power stations, the following criteria are also considered: – Type of fuel, – Year of construction and/or efficiency, – Location/nodal point. To analyse future situations with high requirements for energy balancing, the following analysis concentrates on the variants with high penetration of renewable energies. Two methodological approaches are used: Roadmapping and temporal exploratory scenarios. The “lead scenario 2009” is a roadmap scenario based on pathway analysis for reaching a certain target. Scenario “III” of Lindenberger et al. (2008) is below named the “political renewable energy sources (RES) scenario”. The political RES scenario assumes an intensified funding of renewable energy sources and applies an economical optimisation process. The considered period of the study and, thus, the optimisation, goes to 2030. It does not consider strong structural changes in the energy supply. Rather, it focuses on an economic optimisation of developments that could be expected if certain political measures are implemented. It does not represent a complete optimisation, because the temporal period analysed is limited to 20 years and induced socio-economic effects as well as environmental externalities, including potentially later occurring impacts from climate change, are not included. Thus, although the study concentrates on economic optimisation, it does not adequately cover the requirements of maximising intertemporal welfare (priority 3 of the operative action rule discussed in Sect. 2.1.2) and furthermore does not address all other priorities derived from the economic aims described in Sect. 2.1 – “Protection from unacceptable damage through compliance with critical limits of load” (priority 1), “Preservation of the total

3.2

The Derivation of Future Electricity Supply Parameters

51

value of produced and natural capital” (priority 2) and “Just distribution of basics at present” (priority 4). The lead scenario 2009 does not only cover a different time period (up to 2050 as opposed to 2030 for the political RES scenario), but also is based on different assumptions. The lead scenario is based on a “back propagation” or “back tracking” approach and can, therefore, be seen as a roadmap to reach the political predefined CO2 reduction target for 2050. Going backwards from 2050, necessary actions and shares of renewable energy use are determined in such a way that by 2050 emission reductions will theoretically be reached. Economic conditions play only a minor role in the scenario. The lead scenario sets the first priority on meeting targets in order to protect the society from inacceptable damages without carrying out a detailed economic optimisation. It thus concentrates on meeting priority 1 of the operative action rule derived in Sect. 2.1 by neglecting the other priorities. It draws a roadmap for realising a system with which it will prospectively be possible to meet the German CO2 targets. The scenarios examined here always assume a “low price variant” for fossil fuels. They assume that there is a low price path for oil and gas and that coal prices stay the same. This assumption implies that coal-fired power stations will decrease in principle and oil and gas power stations will increase in number. There is an explicit analysis of this in Sect. 3.2.3. Because of the very long time periods covered, the accuracy of the scenarios cannot be assured. The aim with using such scenarios is to get ideas about what could be typical future developments when the electricity system is restructured to include high renewable electricity inputs and where balancing needs are large. A short description of the assumptions in the two scenarios follows.

3.2.1

Assumptions in the Political Renewable Energy Sources (RES) Scenario: Intensified Funding

In the case of the political RES scenario, environmental protection and the withdrawal from nuclear energy are prioritised. It is assumed that the renewable energy law is pushed by higher funding rates and advanced emission reduction goals are reached. It is further assumed that the ratio of combined heat and power (CHP) to the electricity generation will double by 2030. The intensified funding of the RES leads to somewhat less addition or the delayed addition of coal and gas-fired power stations.

3.2.2

Assumptions According to the Lead Scenario 2009

The lead scenario 2009 is intended to clarify the fluctuation range of the assumptions based on different studies and clients. In the study carried out by the German Aerospace Center (DLR) on behalf of the German Federal Environment Ministry (BMU), the renewable energy sources still have a much higher proportion

52

3

Existing Energy System Studies

than in the RES variant. The potentials for consumption-side efficiency increase are also estimated much more optimistically here. Moreover, the period considered in the study runs until 2050, meaning that a long-term forecast is made for 2030 and beyond on this basis. This is referred to here as 2040þ to make it clear that not a specific point in time is concerned, but a possible situation in 2040, 2050 or even as late as 2060.

3.2.3

Effects on the Conventional Power Station Park

The development of conventional power station parks is affected considerably by the political and economic framework conditions assumed in the individual scenarios. Due to the ever more strongly increasing and fluctuating (i.e., not entirely predictable) feed-in from renewable energy sources, preferentially from wind and photovoltaics (PV) in the political RES scenario and the lead scenario, the power supply can be expected to change constantly. The intensified funding of renewable energy sources leads to a decrease in need for conventional power stations, since these can be partially replaced with renewable energy sources. The assumptions for fuel and CO2 prices are of high importance, particularly when deciding between building new hard coal-fired stations and gas and steam power stations (GS power station), which are both used in the medium-load range. If a low gas or oil price is established while at the same time the price of CO2 is high, the economic efficiency for GS power stations increases compared to hard coal-fired power stations. The aim of this study is to work out the future annual curve of the share of load which can be covered by the feed-in from conventional power stations and by the feed-in from renewable energy sources in the time horizon until 2040þ in the two scenarios. A future fuel price path is also defined. The resulting data serve as a basis for looking at the balancing options, such as energy storages and the load management options, in more detail in the course of this study.

3.2.3.1 Renewable Energy Sources The assumed development of the annual electricity generation from renewable energy sources for the selected scenarios is shown in Fig. 3.3. The amount of annual electricity generation is presented for 2020, 2030 and 2040þ, compared to actual values for 2008. It is evident that the generation of renewable energy sources in the lead scenario is clearly higher than for the political RES scenario variant. Both the photovoltaic proportion and the offshore wind production are estimated much more optimistically than in the other scenarios. Furthermore, the import of electricity from renewable energies is only considered for the lead scenario. Solar heat from North Africa (i.e., “DESERTEC”) and wind energy from neighbouring countries are included. For the rest of the study it is assumed that imported power from renewable sources in general does not provide controllable base power. Maybe solar thermal installations, as planned by DESERTEC, with thermal storage facilities could in future provide controllable power so that demand and supply

3.2

The Derivation of Future Electricity Supply Parameters

53

Annual electricity generation [TWh]

600

500 EE import

400

Photovoltaics Wind offshore

300

Wind onshore Geothermics

200

Biomass Water

100

Load

0 actual values 2008

political RES scenario

lead political RES scenario scenario

2020

lead scenario

2030

lead scenario 2040+

Fig. 3.3 Scenarios of electricity generation from renewable energy sources and total consumption forecast (load)

can be balanced. However, this cannot be expected from European wind or solar power (see Chap. 3). Assumptions regarding the development of electrical loads are also shown in Fig. 3.3. The values assumed in the political RES scenario are much higher than those in the lead scenario. Based on 2008, the electrical load for the lead scenario will go down by 2020 by 11%, by 2030 by 15% and by 3% in the reference year in 2040þ despite there being new consumers for electric vehicles. An assumption of 20 million electric vehicles with a resulting energy requirement of approximately 30 TW h in 2040þ is made.2 It is further assumed that city vehicles will be either fully electric or hybrid and use electricity only part time for average daily distances but not for long-range drives. In the scenario, it is supposed that these vehicles use an amount of electricity necessary to travel 8,000 km/year.

3.2.3.2 Fuel Prices Typical fuel price developments are needed to evaluate electricity market behaviour and the value of balancing mechanisms. The values should be plausible, but the precision does not need to be very high for the qualitative assessment. The development of the conventional power station park is considerably affected not only by the renewable energy sources, but also by the fuel price. Figure 3.4 shows

2

Only short tracks are accounted for, long tracks are assumed to be driven with hybrid technology.

54

3

50

Existing Energy System Studies

Fuel oil

Price [ /MWh]

40 DLR Lead 30

EWI REF EWI OIL

20

IER 10

average value

0 2000 25

2010

2020

2030

Natural gas

Price [ /MWh]

20 DLR Lead 15

EWI REF EWI OIL

10

IER 5

average value

0 2000 10

2010

2020

2030

Hard coal

Price [ /MWh]

8 DLR Lead 6

EWI REF EWI OIL

4

IER 2

average value

0 2000

2010

2020

2030

Fig. 3.4 Comparison of fuel price paths (K€ uster et al. 2007, own representation)

the price formations to be expected for the coming years. The three most important raw materials (fuel oil, natural gas and hard coal) are used as references. The fuel price paths considered are based on further scenarios besides the lead scenario taken from K€ uster et al. (2007). A list of the applied scenarios can be seen in Fig. 3.4. The calculations in this study are based on the average values of the respective prices in the scenarios, shown by a dashed line. The middle, inflationadjusted growth rate from 2010 to 2030 amounts to 1.1–1.2%/annum for fuel oil

3.2

The Derivation of Future Electricity Supply Parameters

Table 3.2 Development of CO2 certificate prices CO2 prices 2020 [€/tCO2] Overall Economic Energy Between 19 and 37 Policy Concept 2030 FEM pilot study 2008 Between 30 and 39

55

CO2 prices 2030 [€/tCO2] Between 27 and 46

CO2 prices 2050 [€/tCO2] 

Between 35 and 50

Between 45 and 70

and natural gas and 0.46%/annum for hard coal. The price path for nuclear fuel grade uranium as well as for brown coal is assumed to be constant. This can be explained by the fact that the variable generation costs based on uranium are in this case very low and, therefore, the price sensitivity can be neglected. There is no market for brown coal since the extracted coal is only used locally for energy generation. The figure also shows that some of the assumptions of the lead scenario, the DLR pilot lead study, are different regarding price paths. The assumptions for the development of the CO2 certificate prices also have strong fluctuations. Table 3.2 lists the prices for the purpose of clarification. Different price paths are assumed in the studies. The Federal Environment Agency (FEM) lead scenario 2009 refers to the underlying CO2 prices of the FEM pilot study 2008. In this study, a price of 32 €/tCO2 for 2030 and 45 €/tCO2 for 2040þ (Nitsch 2008) is assumed in all variants.

3.2.3.3 Resulting Power Station Parks In Fig. 3.5, power station parks are represented based on the outcomes of the two future scenarios. The results are influenced by the factors described in the previous sections (i.e., the development of renewable energy sources and fuel price developments). Figure 3.5 represents conventional power stations (e.g., oil, gas turbine) with their corresponding installed power from 2008 to 2040þ. The fact that the installed power of the power stations is lower in the lead scenario than in the political RES scenario can be seen clearly. This is justified by the even higher feed-in from renewable energy sources than is already the case in the political RES scenario. In the political RES scenario, base-load power stations, such as nuclear power, brown coal and hard coal, will still be around in 2030. For this reason, the current operating principles (e.g., dispatching, reserve power provision) will not change dramatically. For the period 2040þ it is expected that the installed power of conventional power stations will go down considerably as renewable feed-in continues to rise and old power stations at the end of their lifespan will not be replaced. The forecast shows that there will then only be a small number of hard coal-fired power stations. Gas and GS power stations will then be increasingly used, as well as a small number of gas turbine (GT) power stations. Some of the installed power of these power stations can then only be used as a long-term reserve, although not as a rotating reserve, for the varying regenerative feed-in (primary

56

3

Existing Energy System Studies

120,000

Installed power [MW]

100,000

80,000 Oil 60,000

Gas turbine

40,000

Hard coal

Gas and gas and steam

Brown Coal 20,000

Nuclear power

0 political lead political lead lead RES scenario RES scenario scenario scenario scenario 2008

2020

2030

2040+

Fig. 3.5 Scenarios of power station expansion

reserve). The extent to which this affects the residual load, the difference between the actual load and the feed-in from renewable energy sources, is discussed in Chap. 3. It will be evaluated whether the residual load can be covered at all times of the day across the different seasons, and whether balancing power is needed, and if so, how much. If more balancing power is needed, this would require further peak power stations or alternative balancing technologies, which are the focus of this study. The represented development paths of the generation structure in Germany are taken as a basis for all further considerations in this study.

3.2.4

Evaluation of Development Paths

The development paths of the various scenarios looked at here differ. The lead scenario does not only set optimistic goals regarding consumption-side efficiency increases, but also in terms of the expansion of renewable energy sources. The consequence is a strongly reduced conventional power station park, with only a small number of base-loadable power stations. The installed power is considerably smaller for the lead scenario in the years looked at than in the political RES scenario. In order to avoid possible gaps in balancing energy in the peak load coverage, measures must therefore be taken. Apart from the addition of peak load power stations, balancing options can also take the form of storage technologies, option load management or the securing of renewable energy imports from abroad.

3.2

The Derivation of Future Electricity Supply Parameters

57

The requirement and potential of these technologies are determined in the course of the study (see Chap. 5). It should be pointed out that these technologies can always be seen as being in competition with the addition of conventional peak load power stations, e.g., gas turbines. The evaluation of alternative technologies must consider both economic factors (i.e., cost comparisons with peak load power stations) as well as their impact on CO2 reductions targets. The load developments in the scenarios lead to different evaluations in terms of CO2 emissions. In the lead scenarios, the consumption-side efficiency potentials (saving possibilities) were assumed to be too optimistic from the authors’ point of view. What initially appears to be profit, is at least compensated for again by the increase in comfort, e.g., air-conditioning systems and increasing information and communications technology (ICT) applications as well as new loads, such as heat pumps or electric vehicles, following unpublished studies. Developments beyond 2020 are afflicted with great uncertainties, meaning that all considerations based on these scenarios should be regarded simply as estimations. Despite the potential inaccuracy of the scenarios, they can be used to discuss the fundamental problems that can be expected in a restructured electrical power supply system. The scale of the requirements for balancing power and the technologies needed can be estimated and evaluated. It is recommended to regularly update the scenarios and developments and to pursue the real power station development. This will be of particular importance because, with Germany’s planned phase-out of nuclear energy, if the addition of new power stations is too small or if there is a delay in the development of renewable energy sources, then there is a risk of a generation gap for Germany. The government may need to take steps to ensure that a sufficient number of renewable energy projects are initiated. It may also need to address problems related to long approval times for power stations and industrial plants making use of renewable energy sources (e.g., offshore wind parks) and investment risks. In sum: A. The political framework conditions (promotion of renewable energy sources, withdrawal from nuclear energy) and the economic framework conditions (fuel prices and market design) are crucial drivers in the development of power station parks. B. Despite certain unavoidable inaccuracies, the scenarios form a good basis for making fundamental analyses concerning energy balancing requirements and projected developments of the total electrical power supply system in the long run. C. The lead scenario 2009 assumes extremely ambitious goals in the development of renewable energy sources and the consumption-side efficiency increases. Until 2030, there will probably be a sufficient number of conventional power stations. However, the share of power plants relying on fluctuating renewable energy sources will strongly increase and, thus, the development of the real generation park must be the subject of continuous attention in order to avoid a gap in coverage. In the scenario 2040þ, only limited installed power from conventional power stations is available. In order to avoid possible gaps in

58

3

Existing Energy System Studies

coverage, additional measures must be taken, such as energy storage, peak load control or the securing of renewable energy imports. These are analysed in the course of this study. D. The scenarios considered only reflect the situation in Germany. From the European perspective, it is assumed that all states will follow individual development paths, but that the share of renewable energy use will increase drastically. Germany can be taken as a model scenario that other ambitious European states may follow. Balancing the fluctuation of electricity supply from renewables and demand can be performed either within the country itself (peak load power stations, load management, storage facilities) or in interaction with neighbouring countries or even the entire European power system (e.g., balancing generation between renewables in different countries, storage in remote areas). In the latter case, a substantial network extension has to be considered from both technical and economical perspectives. Alternatives for running a stable system are considered for the European system, even if the scenarios are restricted to Germany in the first instance. In a further step, a totally new scenario for the entirety of Europe based on a green field approach will be added to estimate overall balancing or storage and transmission needs in Europe (see Sect. 4.2).

3.3

Summary and Conclusions

As sovereignty concerns continue to exert a strong influence on the energy policies of individual European states, for the foreseeable future, energy policy decisions will continue to be determined primarily by national activities. Still, these decisions will have to be made within the political framework of the European Union, which is slowly gaining greater competencies on energy matters. The European energy system will be generated primarily by national policies, but with coordination facilitated by the European Union and with some directives and regulations limiting the scope of individual national actions. In order to facilitate the design of appropriate national policies for low-carbon and renewable energy-dependent electricity structures, scientific scenarios are developed. The analysis of published scenarios for Germany as a country that strongly promotes the use of renewable energies shows that diverse approaches are used. Temporal exploratory scenario building is applied with energy economic models for the analysis of the next 10–20 years (up to 2020–2030). Modelling of further developments in the direction of a viable renewables-based electricity system beyond 2030 (up to 2050) usually applies a predefined targeted system and shows potential pathways for realising the envisaged system. It is important to keep in mind, however, that the framework conditions that have to be assumed for the economic modelling are uncertain and radical changes could occur. This is especially true for any predictions extending beyond about 2030. However, the analysis also showed that only a small number of institutions provide scenarios and the assumptions are usually not consistent.

3.3

Summary and Conclusions

59

In order to make the analyses more usable for policy decisions, it would be useful if the most influencing assumptions were identified and sensitivity analyses were carried out, e.g., analysing the influence of applying different assumptions for cost reductions with technological developments, i.e., learning curves, on the results. For the current study, framework conditions concerning the electricity supply are taken from two scenarios with a high share of renewables in the system, the lead scenario 2009 used to derive a roadmap in Nitsch and Wenzel (2009) and a political scenario with ambitious environmental policy (scenario “III” from Lindenberger et al. 2008). The two scenarios form a good basis for the analysis concerning the balancing energy requirement with a high share of renewable energies in the system in 2030 and a future year not further specified and called 2040þ. In terms of the power generation portfolio it can be seen that at least following the scenarios of the “Leitstudie”, in 2040þ additional measures have to be taken to support the power system. These additional measures could be the development of energy storage capacity, peak load control or the securing of renewable energy imports. These issues are part of the main focus of this study.

.

4

Demand for Balancing Electrical Energy and Power

One important estimate to consider when trying to determine the most appropriate policy options is in which cases, and to what extent, a demand for balancing electrical energy and power exists which cannot be covered by the installed energy conversion systems themselves. Two approaches are followed in this analysis. The first builds on existing and published scenarios for the German electricity sector in the European context, namely those which have been identified in Chap. 3 as being applicable for the analysis, the lead scenario and the political RES scenario (Sect. 4.1). The second approach tries to build up an optimal system of conversion from renewable energies, energy storage systems and transboundary transport of electricity. It does this by developing and using a rough optimisation model (Sect. 4.2).

4.1

Assessing the Balancing Demand and Storage Employment Based on Scenarios for Germany

The scenarios that were presented in Chap. 3 (political RES and lead scenario) are investigated in Sects. 4.1.1 and 4.1.2, first in terms of their residual load structure and their temporal load curve. These sections examine the extent to which the residual load is covered by the conventional power stations available in each of the scenarios. Special analytical attention is given to the lead scenario, since gaps in coverage emerge due to the increase of fluctuating feed-in and the reduced number of conventional power stations. In order to solve this problem, the analysis examines how much balancing power and balancing energy is needed in the course of the year to cover the currently assessed residual load. Balancing power and balancing energy are necessary to establish the balance between supply and demand, which involves bringing the varying feed-ins from wind and photovoltaics in line with the load. Furthermore, the analysis indicates how many storage or peak load power stations are necessary to achieve the balance, even in situations of low wind input. B. Droste-Franke et al., Balancing Renewable Electricity, Ethics of Science and Technology Assessment 40, DOI 10.1007/978-3-642-25157-3_4, # Springer-Verlag Berlin Heidelberg 2012

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4 Demand for Balancing Electrical Energy and Power

It should be noted that the discussion is conducted from a purely German point of view. The alternative options of peak load power stations, load management for lowering the residual load, energy storage possibilities as well as the secured import of energy from abroad are to be considered for load coverage. For the time being, the location of the energy storage systems is not crucial for the provision of power, as storage in Germany is equivalent to storage abroad if the source is connected via a sufficient line capacity. The import of secured energy from abroad is problematic. This is because on a calm wind day in Germany, excess renewable energy may not be available from European neighbouring countries either, due to weather conditions. Only special systems, such as the Desertec project, using concentrated solar thermal power would have the potential via thermal storage capacity to provide secured energy.

4.1.1

Assessing the Demand of Balancing Electrical Energy and Power

This section deals with extreme cases. It examines how much energy must be stored, and at which amount of power or, alternatively, must be provided by rarely operating peak power stations to ensure the security of supply.

4.1.1.1 Effect on the Residual Load and the Available Power Station Power The aim of this subsection is to determine gaps in coverage that arise, i.e., the number of cases where the residual load cannot be covered at any time by the available conventional power stations within the defined scenarios. Based on the gaps in coverage found, balancing options such as energy storage units, peak load power stations or the option of load management are evaluated by this study. The proportion of the feed-in from renewable energy sources as well as the energy quantities of the actual electrical load have already been discussed in Chap. 3 for the two scenarios and serve here as a basis for the residual load calculations (consumption load less feed-in from renewable energy sources). Using scaled profiles (load and feed-in profiles) the annual energy quantities are converted into hourly time-variation curves. The profiles contain so-called “type days” – individual extreme cases are therefore not considered. Each representative year consists of 3 days (Saturday, Sunday and one working day) of each season (winter, spring, summer and autumn). Twelve typical average days within a year result from this. The consideration of 12 typical days means there are 288 hourly values for the examination of the residual load. When dimensioning the necessary storage capacity (see Sect. 4.1.1.3), the starting basis consisting of selected extreme days or extreme periods may not be disregarded so as to ensure that the system maintains its secure supply of energy in such situations. Possible gaps in coverage would thus be ruled out from the beginning. The absolute extreme values are therefore considered separately.

4.1

Assessing the Balancing Demand and Storage Employment

63

The volatile and prior-ranking feed-in from renewable energy plants leads to a less favourable residual and stochastic load structure, which is to be balanced out by the conventional power station park (EEG 2008). Because of this, the conventional power stations have an increasingly volatile operation, which is shown by increased startup processes and partial load operations. The ability to plan the power station dispatch is decreased by the varying feed-in (Lindenberger et al. 2008). In order to identify possible gaps in coverage within the two future scenarios, the minimum and maximum hourly average values of the residual load must be related to the minimum available power station power (without pump storage stations (PSS)). Figure 4.1 illustrates this situation. The minimum available power is the secured power station power. This means that the following factors are subtracted from the installed power: – Control power to be kept available, expected values for revisions – Outages and cooling water availabilities. It can be seen that the maximum and minimum residual load in the lead scenario assumes much lower values than in the political RES scenario, due to the high feedin from renewable energy sources. The fluctuation range is not significantly higher, however. For the lead scenario for 2030 and 2040þ, it is worth noting that the available power station power can fall below the residual load and the requirement can therefore not be covered by secured generation plants within Germany alone. Due to the already mentioned fact that the profiles used do not represent extreme situations, it is quite possible in reality for the residual load to have to be set higher in some extreme situations than is the case here. If, in addition, revisions or even power station failures become frequent on the power station side and thus the secured power is far less than the power assumed here, this can lead to a considerable gap in coverage (power deficit) or to an extreme dependence on electricity 80

Power [GW]

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political RES scenario

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Minimum available power station power (without PSS)

Fig. 4.1 Fluctuation range of residual load and the power station power available in each case

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4 Demand for Balancing Electrical Energy and Power

imports. If the electricity import is to be regarded as unreliable due to power shortages in the neighbouring countries at the same time, for example, storage or peak load power stations or the option of load management are required to provide the necessary balancing power. In Sect. 4.1.1.2, possible extreme situations due to wind calms lasting several days are analysed in more detail. In addition to the temporary power deficit specified, a negative residual load arises in the lead scenario in certain hours where the feed-in of renewable energy is significantly high. In 2030, the value is up to 13.7 GW and, in 2040þ, even 24.0 GW. A negative residual load has the consequence that Germany’s load is too small during certain hours and that a surplus from renewable energy sources is therefore available. The residual load is negative in 54 out of 288 simulated hours in the lead scenario in 2030. This corresponds to approximately 19% of the time considered. A power balance is achieved by limiting the feed-in from renewable energy sources at all these times. The residual load is thus limited to a minimum value of 0. The consequence of this restriction is that approximately 1.4% (4 TWh) of the total feed-in from renewable energy sources cannot be used in Germany, although it can possibly be exported depending on the overall European scenario. In the scenario 2040þ, a negative residual load results approximately 39% of the total time. Approximately 4.7% (21 TWh) of the feed-in could not be used through limiting the negative residual load factors to 0. Below, the two scenarios are examined regarding the composition of their available power station power. Based on the respective conventional power station park of the scenarios, the available power is represented and shown relative to the total network load or the residual load (see Fig. 4.2). The range between the maximum value of the residual load and the network load illustrates the mixing effects between the curve of the actual load and the feed-in from renewable energy sources. The maximum network load is reduced by the feed-in from plants using renewable sources. The maximum and minimum value of the residual load is therefore to a considerable extent determined by the feed-in from renewable energy sources. The following discusses which renewable energy sources are to be regarded as secured. Biomass and hydroelectric power plants in particular are plants that can be controlled and planned. The residual load is lowered considerably due to the high availability and thus secured power of these plants. This is different in the case of wind power and PV plants. Electricity is generated from the current respective power available (wind velocity, radiation intensity), which fluctuates according to natural variations and, thus, usually does not meet changing demand (B€ unger et al. 2009). At unfavourable times where demand rises considerably (peak load), it is therefore possible that the wind and PV feed-in tends towards zero and that the crucial point of the residual load can therefore not be covered. In Nabe (2006), the secured power of wind power plants is given as values between 3% and 20% of the installed wind power. This quantification of the wind power effects is critical. Due to the uncertainty, the determined values are to be interpreted with caution. In order to better examine the usefulness of storage

4.1

Assessing the Balancing Demand and Storage Employment

65

100 Power [GW] Oil Gas turbine

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-20 -40 Installed power

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20 4 0 +

Fig. 4.2 Composition of available power station power

possibilities, a worst-case estimation is made on the basis of real wind calms (see Sect. 4.1.1.2). The wind calms are analysed and discussed in terms of their effects. Figure 4.2 shows that problematic gaps in coverage arise even in the lead scenario without extreme situations being taken into account. A calculated secured power of 7 GW in 2030 and of approximately 18 GW in 2040þ is lacking. This level must be covered by additional measures. No problems arise in the political RES scenario. The residual load is covered by the secured power station power. Therefore, this scenario is given no further attention. In summary, it is shown that the residual load cannot be covered in the lead scenario at all times in 2030 and 2040þ by the power available from the secured power station. Stored electricity or additional peak load power stations (see Sect. 4.1.1.3) are necessary in order to establish a balance between generation and consumption. Moreover, the secured power that is lacking could also be provided by a secured import of fuels or electricity from renewable sources. The consideration and interpretation of this import is a crucial factor influencing developments. It is therefore discussed in Sect. 4.1.1.3. Alternatively, the peak of the residual load can also be reduced by load management (see Sect. 5.3). The residual load is negative in several of the 288 simulated hours of the year. Situations therefore result where the feed-in from renewable energy sources exceeds the load. Without storage systems, the power available free of charge from renewable energy sources would have to be restricted.

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4 Demand for Balancing Electrical Energy and Power

Both the power deficiency (2030: 7 GW and 2040þ: 18 GW) and the power surplus (2030: 13.7 GW and 2040þ: 24 GW) in the lead scenario offer potential for using electrical storage facilities.

4.1.1.2 Characteristics of Possible Wind Calms Lasting Several Days Below, the lead scenario will only be dealt with in terms of its characteristics. This scenario is predicated on an integration of additional storage capacities or peak load power stations as well as the option of load management into the existing power station park in order to cover residual load peaks. The major residual load peaks causing gaps in production are caused by wind calms of up to several days, which are analysed in this section. To get an idea of the size of the production gap, the power and energy are investigated by assuming that they are covered exemplarily by an energy storage system. In general, the function of a storage facility is equivalent to a technical system that can provide positive and/or negative control power to the grid. Therefore, all technologies beyond the classical storage systems that take up electrical energy and supply electrical energy are considered here as synonyms of classical storage. In order to model the lead scenario 2030 and 2040þ in relation to the employment of storage units, it is first necessary to determine the required dimension of additional energy storage options (power and storage capacity). In this subsection, the characteristics of possible wind calms lasting several days are analysed in terms of storage dimensioning on the basis of synthetic offshore wind feed-in data. The modelled wind feed-in is based on historical data on the wind velocities in the North Sea area. The regional wind velocities are converted into feed-ins using wind park models. Real smoothening effects are taken into account by the use of several measuring points. The sample size of the calculations covers 43,800 hourly values altogether from 2002 to 2006. The procedure is described in detail in Brodersen (2008). The maximum length (consecutive hours) of wind calms resulting in a wind feedin below a defined boundary is of relevance for the storage dimensioning. Figure 4.3 shows the annual frequency of calms with minimum durations between 12 and 72 h and limit powers from 1% to 20% of the installed power. Hence, 12-h calms with a feed-in below 1% of the installed power occur around five times a year within the offshore range. If the boundary looked at is 10%, 72-h calms occur about once a year. Further analysis must therefore answer the question of whether a relatively short calm with very low feed-ins or a longer one with somewhat higher feed-ins represents a more critical case for the storage dimensioning. The case relevant for the storage dimensioning is the maximum duration of wind calms observed. The model data shows that, with a boundary of 1% of the installed power, the maximum duration of such a calm is 31 h, whereas a 20% calm can last up to 218 h. 4.1.1.3 Dimensioning the Necessary Storage Capacity In order to dimension the theoretical maximum of necessary storage capacity during the wind calms as a synonym for controllable power for a certain time

4.1

Assessing the Balancing Demand and Storage Employment

67

70

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60 50 1% 40

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10 0 12h

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Fig. 4.3 Annual frequency of long-lasting wind calms in the offshore range (Data source: GKSS, Ecofys; graph by author)

interval, an extreme case is constructed for the type days described in Sect. 4.1.1.1, unlike with the use of the feed-in profiles. The considerations are carried out for the lead scenario in 2030 and 2040þ, where the use of the profiles has already identified a possible gap in generation. The hourly course of the network load in the period around the annual maximum load forms the basis of the considerations. For this purpose, the load curve from 2007 is scaled to 2030 and 2040þ using the annual energy quantity, that is, with consumption by electric vehicles being taken into account. This load is covered by the conventional power stations available in this period (without pump storage stations), as well as the feed-in from use of renewable energy sources and combined heat and power plants. Water, biomass and geothermal facilities are set as having constant feed-in, whereas the PV feed-in is set to zero, since no feed-in is to be expected during the winter maximum load at 18:00 h. The wind feed-in corresponds to the percentage limit value of the calm, whereby this value is also transferred to the onshore feed-in. The CHP feed-in is set according to the heat requirement profile in winter. With respect to the lacking amount of power, the case of 1% calm, irrespective of its length, is relevant. With the assumptions mentioned, a maximum power deficit of 18 GW results for the lead scenario for 2030 and of 35 GW for 2040þ. Since approximately 7.5 GW power (including 1.1 GW in the Vianden power station in Luxembourg) is currently available in Germany from pump storage stations, an additional power of 11 or 28 GW would be necessary. The effective storage capacity available today for the so-called revolving operation – the balance of daily fluctuations as opposed to the seasonal accumulating of river courses – is indicated in Tiedemann et al. (2008) and B€ unger et al. (2009) as approximately 40 GWh, whereby 5 GWh in the Vianden power station are also taken into account here. All characteristics of the wind calms are taken into account for determining the necessary storage capacity so as to be able to substitute peak load power stations.

68

4 Demand for Balancing Electrical Energy and Power 700

Required Capacity [GWh]

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100 0 1

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Fig. 4.4 Required storage capacity for the substitution of peak load power stations (lead scenario 2030)

Figure 4.4 shows the capacity as a function of the additional storage power and corresponding power station power for the different calms. This means that, for 1 GW additional storage power, 10 GW power station power is necessary to cover the gap of 11 GW in 2030, so that the load can be covered at all times. The additional storage structures must have a capacity of at least 81 GWh in order to substitute 1 GW of power station power. If 11 GW of storage capacity is installed, no further power stations are necessary provided the storage plants have a capacity of more than 617 GWh available. In all variants looked at, the 5% calm with a length of 87 h represents the dimensioning case for the amount of energy required. The order of magnitude and the high capacity-power ratio are to be considered for the results mentioned. To aid comparison: the current largest pump storage station in Germany, Goldisthal, has, with 1,060 MW of power, a storage capacity of approximately 10 GWh, which corresponds to 10 full load hours. In the lead scenario in 2040þ, the capacities increase again considerably and amount to almost 1,700 GWh at the peak, if 28 GW power is to be completely replaced with storage (see Fig. 4.5). In this case, the 20% calm with a length of 218 h becomes important for the necessary capacity. The predictability of calms is critical when incorporating stored power, since the storage facilities must have sufficient storage volume and must be filled, from the start, as full as possible. Thus the values shown represent a worst-case situation, although the restriction applies that the calms must also be forecast with a certain lead time. Looking at technology options available today, compressed-air storage systems in particular can be applied for the energy quantities represented, as well as pump storage stations. In Germany, the potential for pump storage is almost exhausted, meaning that at best the power and capacity of existing plants can be increased within certain limits. Planning for various new building projects is taking place in Austria and Switzerland.

4.1

Assessing the Balancing Demand and Storage Employment

69

1,800

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1,000

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400

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Fig. 4.5 Required storage capacity for the substitution of peak load power stations (lead scenario 2040þ)

The potential for compressed-air storage in Germany is also restricted with regard to the necessary rock beds and formations, although an extremely optimistic potential in the North German Plain of approximately 3 TWh is indicated in Wolfhart and B€usgen (2007). In the estimations presented, the import of fuels and electricity from renewable sources, which contains a considerable energy quantity for 2040þ in particular according to Chap. 3, has been left out of the discussion up until this point. It must be considered, however, that wind calms in particular can also affect Germany’s neighbouring countries (especially the Netherlands and Poland) in the same way. There is thus no possibility of an additional importation from these countries if needed. It is also unclear to what extent the import from solar thermal power stations from the Sahara is to be regarded as secured power. Thus even qualitative estimations cannot be seriously made as to what extent the necessary power of 28 GW for 2040þ can be decreased by importation of fuels or electricity from secured renewable energy sources. Finally, the following can be said by way of evaluation: – In the lead scenario in 2030 and 2040þ, situations arise where the feed-in from renewable energy sources exceeds the load. This results in a potential for energy storage. By contrast, the renewable feed-in would have to be restricted if there were no up-to-date possibility of exportation or storage. – In the lead scenario, a calculated secured power of 7 GW in 2030 and 18 GW in 2040þ is lacking when carrying out a type day calculation. If looking at extreme values of calms, 18 GW in 2030 and 35 GW in 2040þ are lacking. These amounts would have to be covered by generation, storage, load control or import measures.

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4 Demand for Balancing Electrical Energy and Power

– If this requirement is to be covered completely by stored power, a storage capacity of approximately 600 GWh for 2030 and of 1,700 GWh for 2040þ would be necessary due to the duration of possible wind calms. This capacity is far out of technically feasible ranges in Germany when applying the current technologies. The location of the storage facility could alternatively be in neighbouring countries, if the transmission capacity can be provided. Further alternative future technological options are discussed in more detail in Chap. 5. – The amount of import of renewable energy that can be assumed to be secured is a crucial factor of influence on foreseeable developments. The large-scale European weather conditions and the transmission capacity have to be considered in the context of this case in detail. Within the accuracy of this study – aiming at assessing only rough results – it can be assumed as a worst case scenario that neighbouring countries will not have large surpluses of renewable energy at the same time that Germany has a high deficit (see, e.g., Hoffmann 2010).

4.1.2

Estimation of the Storage Employment

In order to estimate the economic benefit of additionally available storage capacity, an optimisation calculation is carried out. This includes both a marginal cost-based power station employment and a time-dependent restriction reflecting the storage filling level. No use restrictions for the power stations are considered in the calculations. Since there are hardly any coal-fired power stations left and only peak power stations in the scenario 2040þ, the simplification seems permissible. The aim of the calculations is to economically evaluate the effect of storing generation surplus caused by high feed-in from renewable sources and to compare it to the necessary investment costs. Within the optimisation model, the storage filling level is only fixed at the beginning and at the end of the year and assumed to be at a 50% available storage capacity. Analogous to Sect. 4.1.1, 1 year is illustrated by 12 typical days (“type days”) with 24 h each. Because of the time dependency, due to the storage filling level, the 288 h are optimised simultaneously, since the sequential solution of each individual hour is not possible. This approach implies perfect foresight over a complete year, in determining the optimal storage and power station employment. The target function to be minimised corresponds to the generation costs of the conventional power stations, which are to be used to cover the given load. The effect of different storage capacities on the annual generation costs, resulting from the optimisation, is to be compared with the investment costs. For this purpose, the investments in the storage system, consisting of a power and capacity proportion, are considered on the one hand, and the possible substitution of peak load power stations on the other. The base case corresponds to the complete coverage of the peak load requirement by appropriate power stations and only the change of investment costs is looked at. Adiabatic compressed air storage (AA-CAES) with a total efficiency of 70% is assumed as storage technology here. Unlike the diathermic compressed air storage that is available today, no

4.1

Assessing the Balancing Demand and Storage Employment

71

additional firing is necessary with this type of storage, since the warmth created during compression is stored. Values of 600 €/kW (power proportion) and 3 €/kWh (capacity portion) are assumed for the investment costs. Investment costs of 800 €/kW are given as a target figure for 2020 in Wolfhart and B€ usgen (2007) and Kruck (2007), and it is assumed here that the costs will go down to the current costs of a diathermic storage by 2030 and 2040. The power of the compressor and of the generator is put on the same level in each case. Gas turbine power stations with investment costs of 300 €/kW are assumed as an alternative for the investment in compressed air storage. The annuity costs are determined for all investments to be made, in order to compare the former to the annual savings of generation costs. A required rate of return of 8% is set for a considered period of 20 years. In addition, there is a residual value after 20 years, since the technical service life of a storage and gas turbine is 40 years. In the case of linear depreciation, the residual value amounts to 50% of the initial investment, and after interest deduction to year 0, a proportion of 89.27% of the total investment remains. This proportion is distributed over the considered period using the annuity factor of 10.19%. The annuity investment costs therefore amount to 89.27% * 10.19% ¼ 9.09% of the investment sum. Two alternatives for storage dimensioning are considered for the calculation: – Variant A: The storage capacity corresponds to 8 full load hours in each case, meaning that the peak load power stations cannot be substituted completely. It is therefore determined for each storage size which additional power station power is still needed. – Variant B: The capacity corresponds to the dimensioning case described in Sect. 4.1.1.3, meaning that with 1 GW storage power, 1 GW power station power can be substituted in each case. Figure 4.6 represents the decrease in the annual generation costs as well as the change of the annuity investment costs for the lead scenario 2030. It is to be taken into account that the vertical axes have different scales, since the additional investment costs are around one order of magnitude above the saved generation costs. The decrease of the total generation costs (the system-wide benefit of storage) can therefore not come close to compensating for the necessary investment costs for storage. Moreover, variant B leads to a higher saving with lower investment costs, which results from the substitution of the peak load power stations. Figure 4.7 shows the results in an analogous form for the lead scenario 2040þ. It can be seen that variant B is economical for the first two cases. Besides the 15 or 16 GW additional storage power, another 13 or 12 GW of power station power is necessary in order to cover the maximum power deficit of 28 GW. Due to the possible substitution of peak load power stations with stored energy and the much higher feed-in from renewable sources compared to 2030, the system-wide benefit of energy storage is within the range of the necessary investment costs. The storage units can be loaded at costs close to 0 in the case of generation surplus, which leads to a strong decrease in generation costs. The storage capacity necessary for variant B amounts to approximately 700 GWh at 15 GW according to Fig. 4.5. Economically, this capacity is hardly feasible within Germany, even if different storage

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600

600 400

400

Δ Annuity investment [million /a]

Reduced generation costs [million /a]

Fig. 4.6 Reduction of the annual generation costs and annuity investments in storage (lead scenario 2030)

15 16 17 18 19 20 21 22 23 24 25 26 27 28 Additional storage power[GW] Reduced generation costs (A)

Reduced generation costs (B)

Δ Annuity investment (A)

Δ Annuity investment (B)

Fig. 4.7 Reduction in the annual generation costs and annuity investments in storage (lead scenario 2040þ)

technologies are combined. If using storage facilities abroad, the additionally required network expansion must also be taken into consideration in the investment. The represented results of employment optimisation underestimate the actual value of storing electricity, since extreme situations are disregarded, due to the

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consideration of only seasonal averaged typical days (type days) with the appropriate feed-in and load profiles. It is in these situations in particular that market prices can go far above the marginal costs of generation due to the supply shortage. A fundamental model as used here is based on the short-term marginal costs of generation. The electrical load is modelled as price-inelastic demand and the last power station in the merit order determines the market price. As a result, no prices above the marginal costs of the most expensive power station arise. These prices are crucial however for the economic efficiency of peak load and storage power stations, since otherwise the peak-load power stations, above all, cannot obtain any coverage contributions. Storing electricity can exert a dampening effect on the price while leading to a positive effect on market results. It should be noted, however, that the assumption of perfect foresight over the complete year leads to an employment pattern of storage facilities that could not be achieved in practice. In conclusion, we see that in the long run, storage facilities will economically become feasible if sufficient surplus power and demand is available and the storage capacity can be used for balancing on a daily base. A detailed assessment would require a peak price model, which is extremely hard to set up for long-term future scenarios.

4.2

Assessing the Storage Demand Based on an Optimised Pan-European Low-Carbon Electrical Energy Supply Strategy

4.2.1

General Aspects and Boundary Conditions

The analysis of the energy scenarios showed that until today no reliable data are available on the total need for energy storage systems in future energy supply scenarios. The main reason is the very high complexity of the topic. The necessary capacity of storage systems depends strongly on the assumptions about the power generation mix, the geographic distribution of the power generators and the capacities of interconnecting grids among different regions. Only if answers to all these questions are given can the amount of storage capacity be derived from these data. The power generation mix must be defined by the amount of fluctuating renewable power generators and fuel-fired power plants. Furthermore, it is necessary to define the region within which balancing of power generation and power consumption should take place. The calculations have a very high degree of complexity due to the high number of uncertainties and the needed detailed data, especially with regard to the weather and the cost data for components of the power system. Existing studies typically define a certain share of renewable power generators in different countries, and based on these assumptions storage capacity is calculated to assure the power balance at any point in time.

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Therefore, we followed an extreme and simplified approach for the calculation of storage capacities on a European level. The assumptions for the approach are as follows: – We assume an “open countryside” approach for the power generation capacities and the trans-national transmission lines. The distribution grid and the timely and geographic distribution of loads are assumed to exist in the way that they do today. Geographically resolved weather data for 7 consecutive years, dealing also with extreme weather conditions are used, providing solar radiation and onshore and offshore wind conditions. – To deal appropriately with the storage systems, a time-step simulation with a time resolution of 1 h over the period of 7 years is performed in any calculation. – For the power plants, only onshore and offshore wind power generators and photovoltaic power generators are taken into account resulting in a 100% renewable scenario. – Maximum potentials for wind power and photovoltaics are taken from studies or the European Commission. Capacities for the storage capacities where not limited to any technical restrictions. – Two different categories of storage systems have been used for the optimisation, which were differentiated by the specific investment costs and the efficiency. Costs and efficiency of “short-term” storage devices were chosen according to pumped hydropower stations, but could also be realised by other storage technologies including batteries, electric vehicles or demand-side management. For the “long-term” storage systems, costs and efficiency were chosen according to hydrogen storage systems. – Europe, including North Africa and the Near East has been separated into 22 geographical regions. Even though the simulation approach would have been able to search for grid interconnection between all regions, we chose 61 connections between regions to limit the calculation time. The chosen scenario is surely an extreme scenario and we do not expect a realisation of the energy supply of the future based on this scenario. A future energy supply structure would include, even in a 100% renewable scenario, controllable power generators, such as hydropower and biomass. Using these controllable power sources will reduce the need for storage devices and will also lower the overall power generation costs. Therefore, the results presented here can be seen as an extreme scenario where only PV and wind power generators are used, including an intelligent interconnection between the different European areas.

4.2.2

Power Flow Calculation

To limit the total calculation efforts, a simplified power flow calculation is used. The structure of the calculation is depicted in Fig. 4.8. In each time step (duration 1 h) the load for the area is balanced in the first step with the actual power production from wind turbines and PV generators. In case energy from the electrical sector is used for powering the mobility sector, either by

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Assessing the Storage Demand Based on an Optimised Pan–European

Fig. 4.8 Schematic representation of the power flow calculation for each area in each time step (P.B.: power balancing)

Load (conventional)

-

1st Power Balance E-mobility

-

Transmission to balance energy

+/-

Storage short

+/-

Limit renewable

PV

Wind Turbine 2nd Power Balance 3rd P. B.

Storage long Transmission between storage of neighbours

+

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4th P. B.

+/-

5th P. B.

-

6th P. B.

If >0 penalty (Final power balance)

direct use of power in battery electric vehicles or by using hydrogen, this is taken into account in the second step of the power balance. This balance is done for all areas individually. Then, in the case of surplus or deficit power, a transmission via the grid to neighbouring areas is made if the connected area can handle this with benefits. “Neighbouring area” means any area that is connected via an HVDC transmission line to the area that is under consideration. All connected areas are announced for an energy exchange. As we assume HVDC transmission lines, the energy flow from area to area can be controlled precisely and is independent from the grid load in other regions. In AC grids the power flow would result from the impedance distribution in the grid. This is significantly more complex and would require always considering the total grid in each time step. After the levelling via the HVDC grid, local storage systems in each area are used for the balancing. Priority is on using the short-term storage. Only if the maximum power to the shortterm storage is taken into account, does the long-term storage enter the game. After using the local storage systems, further attempts are made to level out deficits or surplus energy with all neighbouring regions (fifth power balancing). If this still results in a remaining surplus or deficit in the respective area, energy is either dumped from the renewable power generators or a remaining deficit is recorded. For remaining deficits, a very high monetary fine is added to the system costs. This assures normally that the optimum solutions always result in system configuration, which totally cover the required load. Ideally, the calculations in all areas, including all grid connections, would be done at each step by a linear optimisation of all power flows. However, as this is very time consuming, we chose this step-by-step approach. We also limit the number of allowed grid connections, to not enlarge the number of variables too much. In total, the energy distribution remains very realistic because the order of power balancing steps is chosen in such a way as to minimise the use of storage

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systems, which would result in additional costs due to their limited lifespan, and to maximise the efficiency (transmissions lines first) which lowers the amount of necessary energy from the renewable power generators. The lower the total efficiency is, the more power from PV and wind is required, which would again increase the costs.

4.2.3

System Optimisation

System optimisation searches for the best combination of installed wind and PV capacity, short and long-term storage capacity (charging power, discharging power, energy capacity) and transmission line capacity in all regions of Europe, including North Africa and the Near East. The simulations are performed for periods of 7 years, based on meteorological data for all regions with an hourly resolution. This also includes data on the electricity consumption in all regions, including an assumed share for electro-mobility. The parameters to be optimised are the following: – Installed PV power capacity (GW), – Installed wind power generator capacity (GW), – Power capacity of HVDC transmission lines from region to region (GW), – Charging power capacity for short-term storage (GW), – Discharging power capacity for short-term storage (GW), – Storage capacity for short-term storage (GWh), – Charging power capacity for long-term storage (GW), – Discharging power capacity for long-term storage (GW), – Storage capacity for long-term storage (GWh). The optimisation is performed by using genetic algorithms. Several sets of parameters (individuals) are generated randomly for the first generation. Each set of parameters is used for a system simulation as a time-step simulation over the 7 years. At the end, the extent to which the required load could not have been served by the defined system is analysed. Unserved load is assumed to generate additional costs. The total costs of the system, including the additional costs for unserved load, are summarised. Sets of parameters with the best total cost numbers are used to generate new individuals, representing a new system design. For generating new individuals, functions known from evolution such as the survival of the fittest, mutation and crossing over are used. In addition, towards the end of the optimisation based on the thus far best result as a starting point, a widely applied simplex algorithm developed by Nelder and Mead is applied for the calculations (Nelder and Mead 1965). This allows for a local optimisation towards the local optimum. The algorithm can also “decide” for each region whether to couple it to other regions with a high-voltage direct current (HVDC) transmission line. The results show that several different system designs result in relatively similar costs per kWh. Therefore, it is no surprise if the system design parameters deviate significantly in different runs of the optimisation.

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Fig. 4.9 Visualisation of a test run, showing the structure, spatial resolution and the type of results which can be awaited of the pan-European model

Figure 4.9 shows exemplarily the results from an early test run on a geographical map of Europe. It gives a good overview about the considered elements and the spatial resolution of the model.

4.2.4

Cost Data and Other Assumptions

The following tables show the cost and lifetime data that have been used for the simulations. For the power generators, costs data have been used that should be achievable, according to different studies, in the coming 30 years, based on foreseeable economy of scale effects and further developments in the existing technologies. Thus, the assumed costs data look forward to the future, but no extraordinary assumptions have been made (Tables 4.1 and 4.2). The short-term storage systems are assumed according to costs of today’s pumped hydropower stations. The maximum allowed storage capacity is eight times the discharge power, resulting in a maximum discharge time of 8 h at full power. The optimisation is allowed to select the charging power, the discharging power and the storage capacities independently for each geographic region. The investment costs for a system with 8 h discharging capacity and similar charging and discharging power would result in 1,000 €/kW. It is well known that most countries do not have sufficient potential to install the necessary amount of shortterm storage as pumped hydro, however it is assumed that the storage capacity

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Table 4.1 General financial data

Parameter Interest rate Maintenance and repair

Assumed value 8% 1% of investment costs

Table 4.2 Definition of power generators

Parameter Wind power generators

Assumed value 1,200 €/kW installed power 20 years lifetime 1,100 €/kW installed power 20 years lifetime

Photovoltaic power generators

Table 4.3 Definition of short-term storage system

Parameter Efficiency charging of storage system Efficiency discharging of storage system Costs for charging interface Costs for discharging interface Costs for storage capacity Lifetime of storage system

Assumed value 90% 90% 300 €/kW 300 €/kW 50 €/kWh 40 years

Table 4.4 Definition of long-term storage system

Parameter Efficiency charging of storage system Efficiency discharging of storage system Costs for charging interface Costs for discharging interface Costs for storage capacity Lifetime of storage system

Assumed value 70% 50% 400 €/kW 400 €/kW 1 €/kWh 40 years

could also be provided by other technologies such as batteries, electric vehicles or demand-side management (Table 4.3) (see also the description of relevant technologies in Chap. 5). The technical and costs data of long-term storage systems are oriented on hydrogen storage systems with electrolysers and hydrogen gas turbines. The storage capacity is limited to a maximum of 60 days at full discharge power. Charging power, discharging power and storage capacity are optimised independently (Table 4.4). The connection of the different geographical regions is assumed to be realised by HVDC overhead lines. The efficiency of the power electronic converters at the beginning and the end of the line are estimated at 99% and the losses on the transmissions lines are 6% per 1,000 km. The grid costs are calculated for the trans-regional connections. The costs for the grids in the regions themselves are not taken into account in the total cost calculations (Table 4.5).

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Table 4.5 Definition of HVDC transmission lines

Parameter Efficiency of power conversion per station Efficiency of transmission Costs for power converter per station Costs for transmission line Lifetime of transmission lines

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Assumed value 99% 94% per 1,000 km 75 €/kW 185,000 €/(GW*1,000 km) 40 years

Table 4.6 Overview of the average results for power supply in Europe including North Africa and the Near East with all available technologies for a 100% power supply from wind and photovoltaics only Parameter Result Wind power capacity 1,457 GW installed Photovoltaic power capacity 1,210 GW installed “Short storage” discharge power 2,404 GW installed “Short storage” storage capacity 5,680 GWh installed (2.4 h full load) “Long storage” discharge power 1,978 GW installed “Long storage” storage capacity 741,107 GWh installed (15.6 days full load) Generation costs per kWh 17.1 €ct/kWh

4.2.5

First Model Results

First runs of the model show its applicability. However, the model is still in the development and some parameters will still have to be analysed in detail before it generates sound results. The first results presented here are very preliminary. Nonetheless, they show which kind of results can be awaited from the model. Assuming the whole of Europe and some parts of northern Africa as the modelling region and all possible technologies (see Fig. 4.9), the costs for the power supply were estimated to be about 17 €ct/kWh, which can be interpreted as first estimate on the order of magnitude for costs of a future energy system consisting only of wind power and photovoltaics, energy storage, and grid connections, and which has to be reconfirmed by further analyses. The total installed capacities for the complete region are shown in Table 4.6. Figure 4.10 shows the installed capacities normalised by consumption. The results in Table 4.7 refer to the best case, which has been calculated among all runs for the specific boundary conditions.

4.2.6

Discussion of Results

The results show that a full supply from renewables is possible, and show the relevance of storage systems in these scenarios. With further model runs it will prospectively be possible to demonstrate that the application of storage systems

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Fig. 4.10 Overview of the results for PV, wind and short and long storage capacities for power supply in Europe including North Africa and the Near East with all available technologies for a 100% power supply from wind and photovoltaics only normalised to the average power consumptions in the different regions. BNL: Benelux, CZE: Czech Republic, DEN: Denmark, DNE: Germany North East, DNW: Germany North West, DSE: Germany South East, DSW: Germany South West, ESP: Spain, FRA: France, GBR: Great Britain, GRE: Greece, HUN: Hungary, ITA: Italy, MEA: Middle East, NAF: North Africa, NOR: Norway, POL: Poland, ROM: Romania, RUS: Russia, SUI: Switzerland, SWE: Sweden, TUR: Turkey

4.3

Summary and Conclusions

81

Table 4.7 System design and operational results for the best case achieved in all simulation runs for Europe Overall results Electricity costs 17.1 €ct/kWh Total investment 5,973 billion € Wind turbines Photovoltaics Installed capacity 1,425 GW Installed capacity 1,270 GW Available full load hours 2,759 h Available full load hours 2,000 h Used/available power 88.8% Used/available power 91.6% Share of total investment 25.6% Share of total investment 20.9% Short storage Long storage Discharge capacity 2,198 GW Discharge capacity 1,860 GW Ratio discharging/charging 1.3 Ratio discharging/charging 1.1 capacity capacity GWh capacity 5,050 GWh GWh capacity 680,600 GWh Full load hours 2.3 h Full load hours 366 h Equivalent full cycles 86 cycles Equivalent full cycles 0.4 cycles Share of total investment 17.9% Share of total investment 26.8% Transmission lines Installed capacity 1,822 GW

lowers the total costs of power generation. First runs indicate that a European interconnection with a strong grid does not necessarily result in the lowest power generation costs for all areas. Some countries may achieve lower power generation costs if they make up their own market. This result could be different if restrictions on capacities of hydropower in the individual countries are considered. The first results of the model are promising with regard to its potential contribution to energy system analysis. It is an example for an approach that is completely different to the traditional ones, but can give interesting insights into the characteristics of potential future energy systems.

4.3

Summary and Conclusions

The analysis of required balancing energy and power in the analysed scenarios revealed that critical situations occur, particularly in the scenarios of the lead study (Leitstudie). A calculated secured power of 7 GW in 2030 and 18 GW in 2040þ is lacking under statistically average conditions. In extreme situations, the gap observed with the used data represents 18 GW in 2030 and 35 GW in 2040þ. Furthermore, situations in which the feed-in from renewables into the electricity grid exceeds the load occur. The calculations result in 4 TWh (1.4% of feed-in of renewables) and 21 TWh (4.7% of feed-in of renewables), which cannot be used in the system. Should the gaps have to be covered completely, estimations based on past situations show that storage units with a total capacity of 600 GWh in 2030 and 1,700 GWh in 2040þ would have to be implemented. Situations with 5% of

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remaining power from renewables in the system determine the required storage capacity for 2030, whereas for 2040þ, depending on the additional power installed, the cases of 5% and 20% determine the capacity required. The requirements are lowered in accordance with the extent to which import of secured electricity from renewable energies can be obtained. Considering compressed air storage as an example, and without peak pricing being taken into account, the investment costs for storage of energy are an order of magnitude higher than the saved generation costs in 2030. For 2040þ, additional storage capacity with a total power of 15 GW is economical if appropriate peak power stations can be substituted. The calculations are based on type days. Taking potential peak prices also into account, which could not be done in the analysis, it is anticipated that the economic benefits of storage application will increase. The pan-European modelling approach shows that applying completely new approaches and models for system analysis can give further interesting insights into the characteristics of potential future energy systems. With 17 €ct/kWh, the order of magnitude of costs has been estimated preliminarily for an energy system using only fluctuating renewable sources (wind and solar radiation) in combination with two types of energy storages, one long-term storage option and one short-term storage option, and sufficient grid connections. First model runs suggest that using storage facilities may lower the generation costs and strong grids may not be the least costly solution for all countries. Some countries may achieve lower costs by establishing their own market. These results have to be confirmed by further analyses. Nonetheless, the first test runs are promising and encourage the use of this and comparable new approaches for the further analysis of future energy systems with a specific focus on the application of storage systems for balancing electricity produced from wind and solar radiation.

5

Technologies for Balancing Electrical Energy and Power

Having discussed the need for balancing electrical energy and power with additional technologies that can provide load adaption, transport of electricity from abroad, or storage of electricity, the following chapter provides an overview of technological options. Section 5.1 develops a classification scheme. Individual technologies are discussed in Sects. 5.2, 5.3 and 5.4, following the differentiation of “storage” technologies providing ways from “electricity to electricity”, “electricity to anything” and “anything to electricity”. Section 5.5 summarises options for demand response and demand-side management, including the bundling of individual technologies. The analysis in Sect. 5.6 reveals the life cycle costs of individual storage technologies. These are discussed in the context of different specific tasks involved in balancing energy and power. A central requirement for a system with a high penetration of renewable electricity suppliers and balancing capabilities is the viability of various technologies. Therefore, Sect. 5.7 analyses, to the extent possible, the future viability of relevant technologies. The environmental effects, resource use and system characteristics according to the indicators derived in Sect. 2.2 are considered.

5.1

Classification of Energy Storage Systems and Systems Offering Positive and Negative Control Power

Storing energy requires specific technologies, which are in general neither cheap nor efficient. Therefore, it is crucial to analyse the different options for storing energy in detail and to select appropriate technologies with regard to demand. The purpose of storage systems is to supply positive and negative control power on different time scales. The term “storage” will be used here to describe a system that can supply positive and/or negative control power to the grid and includes also technologies beyond the classical storage systems, which take up electrical energy and supply electrical energy. Certain storage technologies can be used for various applications. For comparison of storage technologies from an economic and technical point of view it is of B. Droste-Franke et al., Balancing Renewable Electricity, Ethics of Science and Technology Assessment 40, DOI 10.1007/978-3-642-25157-3_5, # Springer-Verlag Berlin Heidelberg 2012

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relevance to define the application of storage technologies appropriately. Different classifications are necessary to specify the storage system application. Three different classifications with three classes each can be defined as follows: A. type and location of storage systems, B. duration and frequency of power supply, C. input and output type of energy to and from the storage system. Class A differentiates the placement of the storage systems and the main objective for its installation. The classes are A1. modular storage systems with double use, A2. modular storage for grid use only, A3. centralised storage systems. “Modular storage” describes those technologies that are made from relatively small basic units. The basic units can be connected together to form larger systems, but neither the efficiency nor the specific costs are reduced significantly when storage system size is increased. Typically, there are no special requirements concerning the location of such batteries other than certain safety issues. In contrast, “centralised storage” technologies are those that are localised at specific sites and have specific requirements concerning the geological structure of the site (e.g., pumped hydro storage systems with two water basins on different levels). Furthermore, these technologies are typically characterised by the fact that efficiency increases while specific costs related to power and energy capacity decrease with increasing system size. Typical systems have an installed power of 100 MW or more. “Double use” indicates that the main purpose for the installation of the storage system is not to supply grid services. The storage systems are installed to serve in a certain application, e.g., such as mobility. Batteries in electric vehicles can be used additionally for grid services, but their main objective is to assure mobility. These storage systems are different, because first of all the operation schemes must take into account their limited availability for grid services, on the other hand, however, these storage systems are typically already financed by their main application. Therefore, the storage systems can serve grid services additionally, but they need not refinance themselves from grid services only. Class B has the following sub-classes: B1. “seconds to minutes” – short-term energy storage, B2. “daily storage” – medium-term energy storage, B3. “weekly to monthly storage” – long-term energy storage. The “short-term energy storage systems” have to supply their energy immediately after it is asked for. Full power is already supplied after a few seconds for a maximum duration of about a quarter of an hour. This allows these storage systems to supply primary control power to the grid or to serve as intermediate storage systems in applications with a high frequency of load changes. The latter could be, for example, cranes, which lift heavy loads, or acceleration and braking systems of trams and subways. The short-term energy storage systems have an energy to power ratio (installed capacity in kWh divided by the peak power in kW – E2P) of less than 0.25 h. Therefore, the storage systems must be capable of high power charging

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Classification of Energy Storage Systems and Systems Offering Positive

85

and discharging and – depending on the application – they can be subject to a huge number of charge/discharge cycles per day. The “medium-term energy storage systems” have an E2P ratio of 1–10 h and therefore the specific load on the storage systems is significantly less. Furthermore, the number of full cycles per day is very limited and rarely exceeds two full cycles a day. These storage systems make it possible to level differences in power generation consumption over the course of a day. Classically, such storage systems are charged during the night and supply additional power to the grid during peak load times (noon and late afternoon/early evening). These storage systems can also smooth out deviations between forecasted renewable power generation and actual generation. In contrast, “medium-term” storage systems cannot assure supply security if insufficient power generation from renewable sources occurs for prolonged periods of several days or weeks. To ensure supply security in such circumstances requires “long-term energy storage systems”. Systems with E2P ratios of 50–500 can supply energy for several days or weeks. Therefore, automatically, the number of cycles per year is very limited. This requires very cheap storage media to allow a refinancing of the storage system. In addition, the self-discharge of such systems should be low. Finally, “inputs and outputs of energy to and from the storage system” can be categorised as follows: C1. “electricity to electricity” – positive and negative control energy, C2. “anything to electricity” – positive control energy, C3. “electricity to anything” – negative control energy. The classification follows the strict definition of “storage systems” as elements in the power supply system, which can supply positive or negative control energy. According to this definition, “electricity to electricity” storage systems can supply positive and negative control energy to the grid. They take electricity from the grid to get charged and they supply electricity to the grid if needed. This is what typically is called a storage system. However, power or negative control energy could be served also by other technologies. “Anything to electricity” technologies support the grid with positive control energy either by shutting down electrical loads, which for the grid is the same as increased power generation capacities, or by supplying additional power to the grids from energy reserves stored otherwise. The latter category includes all conventional power plants, which can supply positive control energy for different periods of time from fossil, nuclear, hydro or biomass fuels. Controlled shutdown of loads can be supplied, for example, by demand-side management strategies or by controlling the charging of electric vehicles. “Electricity to anything” technologies use electrical energy and convert it into an energy carrier with a lower exergy level. The exergy level could be as low as zero, which is equivalent to the shutdown of a renewable power generator. However, the category also includes the generation of heat from electricity or the generation of chemical fuels from electricity, such as hydrogen or methane. A combination of an “anything to electricity” and an “electricity to anything” storage technology can provide the same services to the grid as an “electricity to

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electricity” storage system. Therefore, it is necessary to compare these technologies with regard to costs and technical potential. In addition, several other points must be taken into account when judging different storage technologies. The most relevant aspects are: – investment costs, – life cycle costs (LCC), – environmental life cycle analysis (LCA), – construction constrains, – overall energy efficiency, – overall impact on power supply system, – CO2 emissions, – national energy autonomy, – social and political acceptance. The various available technologies are listed in Tables 5.1, 5.2 and 5.3, based on the three main categories discussed above. Generally, all technologies belonging to a certain “duration and frequency” category (“seconds to minutes”, “daily” or “weekly to monthly”) are in direct competition to each other. By intelligent management, the modular storage systems can provide the same services to the grid as the centralised storage technologies.

5.2

Technical Description of “Electricity to Electricity” Energy Storage Technologies for a Balanced Electrical Energy and Power Supply

This chapter discusses the different technical options for balancing the power supply and power demand in the grid. First, the different storage technologies for electrical energy are discussed. The technologies are classified as found in Table 5.1. Before looking at the different storage technologies in detail, it is worth having a look at the typical energy densities achieved with different classes of storage technologies. The comparison shows that chemical storage systems have, beside some options of heat storage, by far the highest energy densities, particularly when stored as liquids (Table 5.4).

5.2.1

“Mechanical” Storage Systems for Electric Power

Central storage systems typically have an installed power of more than 100 MW and typically are connected to high or extra high-voltage grids.

5.2.1.1 Compressed Air Energy Storage (CAES) Compressed air energy storage systems use power to compress air and store it under high pressure. If power is needed from the storage system, turbines generate electricity by depressing the compressed air. Compressed air storage systems can

Centralised storage technologies

Modular storage technologies for grid control only

Modular storage systems with double use

Typical time scale/energy-to-power (E2P) ratio “Seconds-to-minutes” “Daily” storage systems storage systems <0.25 h 1–10 h 1 kW–1 MW – electric and plug-in hybrid vehicles – electric and plug-in hybrid vehicles with bi-directional charger with bi-directional charger – grid-connected PV-battery systems – grid-connected PV-battery systems (e.g. lead-acid, lithium-ion, NaS, (e.g. lead-acid, lithium-ion, NaS, redox-flow, zinc-bromine batteries) redox-flow, zinc-bromine batteries) 1 kW–100 MW – flywheels – lead-acid batteries – (lead-acid batteries) – NaS batteries – NiCd/NiMH batteries – redox-flow batteries – EDLC (“SuperCaps”) – zinc-bromine flow batteries – lithium-ion batteries – lithium-ion batteries 100 MW–1 GW – compressed air (diabatic or adiabatic) – pumped hydro

“Electricity to electricity” storage systems only

Table 5.1 Classification of electrical energy storage systems (positive and negative control power)

Type of construction/typical power

– pumped hydro

– hydrogen

– redox-flow batteries (?)

“Weekly to monthly” storage systems 50–500 h

5.2 Technical Description of “Electricity to Electricity” Energy Storage Technologies 87

Modular storage technologies for grid control only Centralised storage technologies

Modular storage systems with double use

100 MW–1 GW – rotating masses and steam reserve of conventional power plants – – – –

gas power plants coal power plants hydro storage solar thermal power plants with heat storage

Typical time scale/energy-to-power (E2P) ratio “Seconds-to-minutes” “Daily” storage systems storage systems <0.25 h 1–10 h 1 kW–1 MW – shut down of electric vehicles – CHP units with thermal storage and PHEV charging – demand side management (DSM) of electrical loads (shut down) – electric vehicles and PHEV (stop charging) 1 kW–100 MW – bio-gas power plants

“Anything to electricity” positive control power

Table 5.2 Classification of technologies for positive control power only

– nuclear power plants – hydro storage

– lignite power plants

– bio-gas power plants

“Weekly to monthly” storage systems 50–500 h

5

Type of construction/typical power

88 Technologies for Balancing Electrical Energy and Power

Centralised storage technologies

Modular storage technologies for grid control only

Modular storage systems with double use

Typical time scale/energy-to-power (E2P) ratio “Seconds-to-minutes” “Daily” storage systems storage systems <0.25 h 1–10 h 1 kW–1 MW – electric domestic house heating – electric domestic house heating or cooling incl. heat pumps or cooling incl. heat pumps – demand side management – demand side management (household and industry) (household and industry) – cooling devices – cooling devices – electric vehicles and PHEV – electric vehicles and PHEV with uni-directional charger with uni-directional charger 1 kW–100 MW – shut down of renewable – hydrogen for direct use (e.g. power generators (wind, PV) in the traffic sector) – methane or methanol made from CO2 and hydrogen – shut down of renewable power generators (wind, PV) 100 MW–1 GW – hydrogen for direct use (e.g. in the traffic sector) – methane or methanol made from CO2 and hydrogen

“Electricity to anything” negative control power

Table 5.3 Classification of technologies for negative control power only

Type of construction/typical power

– hydrogen for direct use (e.g. in the traffic sector) – methane or methanol made from CO2 and hydrogen

– hydrogen for direct use (e.g. in the traffic sector) – methane or methanol made from CO2 and hydrogen

“Weekly to monthly” storage systems 50–500 h

5.2 Technical Description of “Electricity to Electricity” Energy Storage Technologies 89

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Table 5.4 Overview of volumetric energy densities of different storage technologies (first order approximations) Storage type Volumetric energy densities [kWh/m3] Mechanical energy storage Potential energy (e.g., pumped hydro with 360 m height difference) ~1 Kinetic energy (e.g., flywheels) ~1 Electrical storage Electrostatic fields (capacitors) ~10 Electromagnetic fields (coils) ~10 Heat storage Sensible heat (e.g., water @ DT ¼ 100 K) 116 Phase changes (e.g., water to steam) 636 Chemical storage systems Lithium-ion batteries ~300 Liquid hydrogen ~2,400 Gasoline ~12,000

have additional heat storage (adiabatic CAES) or they can use the heat needed during expansion of the air to avoid icing on the turbines from a conventional natural gas-fired turbine (diabatic CAES). The latter can achieve efficiencies in the order of 55% because the compression heat gets lost. Adiabatic CAES with high temperature heat storage can achieve efficiencies of up to 70%. (It should be noted that they are still, however, in the R&D phase; no real-size system has yet been deployed.) The losses are high due to heat generation during compression of the air. The compressed air is typically stored in underground caverns. Especially caved salt domes are an interesting technical and economical solution. However, this also restricts possible locations for CAES to areas with an appropriate geological formation for the air storage. Germany has many salt domes in its northern regions. This coincides well with the major potentials for wind power. Two diabatic CAES are in operation worldwide, several major utilities plan demonstration plants with adiabatic CAES in Germany for 2016–2018. According to Table 5.1, CAES are centralised “daily” storage systems.

5.2.1.2 Pumped Hydropower Plants Pumped hydropower plants are today the backbone of the power grid and provide almost all the storage capacity used in the power grid. Water flows between an upper storage lake and a lower reserve basin either by natural gravity through turbines (during power generation for positive control power) or by pumps (when consuming energy and storing it in the upper storage lake for negative control power). The upper lakes are either natural lakes with natural feeders or artificial lakes that are only supplied by pumped water. A typically sized pumped hydropower station using an artificial lake can provide full power for about 8 h either in the one or the other direction. The power generation can be controlled continuously

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over a wide power range. In older systems the pumps can hardly be controlled. They either work or they do not. To adapt the power to the required negative control power, the pumped hydropower station can either use different available pumps or the power station generates, in parallel, power to adjust the net power consumption (“water short circuit”). This results in relative low efficiencies. With the newest technologies for the motor, pump and power electronics, it is possible to adjust the pumping power continuously and to reach an efficiency level of around 80%. Typically, pumped hydropower stations are used today for levelling the difference between predicted and actual power profiles as well as for energy trading. This usually involves buying cheap energy from the grid during the night and selling it back during the peak load hours of the daytime. The systems with artificial lakes without natural feeders typically are sized to serve peak power for about 8 h. This size is, however, far from sufficient for supplying power during periods when there are several days of low wind speed. This would require significantly larger water reservoirs than are available today at lakes with dams and natural feeders. These existing systems would need a retrofit with pumps to become pumped hydro storage systems. An important question is how to get access to a sufficiently large water basin if no lower lake is available. Long caved pressure tunnels might be a solution, but it would be necessary to analyse the options in each case in detail with regard to the cost effectiveness. According to Table 5.1, pumped hydropower plants are centralised “daily” or “weekly to monthly” storage systems.

5.2.1.3 Hydro Storage Systems Huge hydro storage plants with natural feeders can be used also for levelling the power grid especially for longer periods of time. This can be achieved by an optimised operation strategy and would require additional turbines, but no pumps, and, therefore, no lower water basin. The optimised strategy would be to generate power only during long-lasting periods when there is insufficient power generation from fluctuating renewables. During other periods, the systems do not generate power or only small quantities, e.g., to assure a minimum water flow in the downstream rivers. As this reduces the number of operating hours even though the amount of water from the natural feeders remains the same, it is necessary to increase the installed power. This option is especially relevant in conjunction with very large hydro storage systems in Scandinavia and the Alps. As can be seen in Table 5.2, hydro storage systems are centralised “daily” or “monthly to weekly” storage systems for positive control power. 5.2.1.4 Flywheels Flywheels store energy as kinetic energy in rotating bodies. The ability of flywheels to store energy is, thus, proportional to the second power of the rotational speed and the moment of inertia of the rotating body. Three different technologies are on the market today. They can be grouped according to the rotational speed: slow rotating flywheels with approximately 5,000 revolutions per minute (rpm), medium rotational speeds with approximately 25,000 rpm, and fast rotating flywheels with approximately 100,000 rpm. However, increasing the rotational speed does not

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necessarily result in a higher level of stored energy, because the radius of the rotating bodies must be reduced with increasing rotational speed. Otherwise the materials of the rotating bodies could not withstand the centrifugal forces. For the medium and fast rotating flywheels, complex composite materials are applied, as also used, for example, in modern aircrafts. Flywheels in power storage systems have no mechanical coupling. The flywheel is accelerated by means of an electric motor, which is used in the case of discharge as a generator. Flywheels are classic high power storage devices, which can deliver very high power for short periods of time. This is very similar to electrochemical double-layer capacitors. The power rating of the flywheels only depends on sizing of the power electronics and the installed electro motor/generator. The number of lifetime cycles is almost unlimited. A major disadvantage of flywheels is the high self-discharge rate. This is due to losses in bearings and the friction of the rotating body. Therefore, vacuum housing and low-friction bearings are used. Depending on the product, it takes several hours for the flywheels to lose 50% of their stored energy. If high numbers of charge/discharge cycles are performed per day, this is not of major relevance, but flywheels are inefficient with regard to long-term energy storage. Table 5.1 categorises flywheels as a modular storage technology for use as “power” storage systems.

5.2.2

“Electrical” Storage Systems for Electric Power

5.2.2.1 Electrochemical Double-Layer Capacitors (“Supercaps”) Electrochemical double-layer capacitors (EDLC) fill the gap between classical capacitors used in power electronics or filters with their almost infinite cycle lifetime and rechargeable batteries with orders of magnitude higher energy density. EDLCs are often called “supercaps” even though this is originally a brand name. EDLCs combine properties from the world of capacitors and electrochemical devices. Energy is stored purely in electric static fields. However, the EDLCs have liquid electrolytes and they use ions for forming the second “plate” of the capacitor. One plate is made from a highly porous carbon material with a very high internal surface and the counter electrode is formed on this active surface by the ions dissolved in the electrolyte. During discharge, the ions move away from the carbon surface. No electrochemical reaction occurs in the cell in normal operation. The energy storage process is simply a physical movement of ions to the surface or away from it. This is the reason for very long cycle lifetimes in the order of a half to one million cycles. It is a system using liquid electrolyte. The liquid electrolyte is not 100% stable and is dissolved on the carbon surface. The reaction rate of this process is strongly correlated with temperature and voltage. The lifetime of EDLCs depends on operating conditions, but is in any case limited. Energy densities of commercial products are typically in the order of 4–6 Wh/kg, however the power density is very high and can go beyond 10 kW/kg. Together with the high cycle lifetime, this qualifies the technology for applications with a very high power demand for short periods of time, but at high cycle numbers. Typical discharge

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times should be in the order of 10s. Therefore, EDLCs can be used, for instance, in hybrid electric applications to support combustion engines during acceleration or for regenerative braking. Besides their low energy density, EDLCs are quite expensive. Prices for EDLCs are in the order of 10,000 €/kWh. Therefore, areas of applications for EDLCs in the power grid are mainly for power quality stability rather than for storing significant amounts of electrical energy. In Table 5.1, EDLCs are designated as modular storage technologies used for “power” storage systems.

5.2.2.2 Superconducting Coils While capacitors store electrical energy in an electrostatic field, coils in general store electrical energy in electro-dynamic fields. The stored energy depends on the current flowing in the coils. As losses are proportional to the current squared, industrial applications of coils as energy storage devices make sense only in cases of superconducting coils. Superconductivity results in zero resistance of the conductors and therefore no losses occur during storage in the coil itself. However, a very deep temperature is required, either below 4 K for classic superconducting materials or in the range of 30–80 K for high-temperature superconducting materials that require either liquid helium or liquid nitrogen. To keep the fluids liquid, a continuous operation of the cooling systems is required and ultimately this produces losses. Even though superconducting coils are an interesting technology from a scientific point of view, it is hardly possible to envision commercial applications in the field of energy storage systems with significant amounts of stored energy as discussed in this study. Therefore, this technology is not listed in Table 5.1.

5.2.3

“Chemical” Storage Systems for Electric Power

5.2.3.1 Lead-Acid Batteries Lead-acid battery technology is the electrochemical storage technology with the highest installed capacity worldwide. Many different applications, such as starter batteries in vehicles in combustions engines, uninterruptible power supplies, forklift trucks or traction applications, are served with lead-acid batteries. Several largescale battery systems in the range of some 10 MW and up to 50 MWh have been installed in the past based on lead-acid batteries. Lead-acid batteries are made mainly from lead, sulphuric acid and plastics. The energy density of approximately 25–35 Wh/kg is low, while the energy efficiency of 80–90% is fair. Stationary lead-acid batteries of high quality can achieve lifetimes of 6–12 years and cycle lifetimes of 2,000, and also, in special cases, more than 7,000 equivalent full cycles. Costs per kWh are today in the order of 100–250 €/kWh for the battery cells depending on the quality. Industrial batteries have recycling quotas near 100%. The secondary lead can be used again for battery production. Two different main technologies are used today: flooded lead-acid batteries with liquid electrolyte and valve-regulated lead-acid (VRLA) batteries

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with internal gas recombination. While the VRLA batteries require significantly reduced maintenance efforts and lower requirements with regard to the ventilation of the battery compartments, batteries with liquid electrolyte achieve longer cycle lifetimes in stationary applications. Large-scale battery systems based on lead-acid batteries have been erected around the world to solve local power quality and power supply problems. This includes battery systems for the stabilisation of grid extension, or frequency stabilisation. The largest battery system, which has been operated in Germany, was the BEWAG system in Berlin. The system was put into operation in 1986 in Berlin with an installed power of 17 MW and 14 MWh energy capacity. This system was used for frequency stabilisation in the island grid of West Berlin. The energy throughput of the battery was almost three times the nominal capacity, or more than 7,000 equivalent full cycles in almost 7 years or operation. Several more similar systems were planned, however, due to German reunification and the connection of the power system of West Berlin to the UCTE grid, the additional systems were not necessary after 1990. Lead-acid batteries have low energy density, low power density and a limited lifetime, but the basic material costs are very low and therefore the technology will retain a dominating position in the stationary battery market in the coming years. According to Table 5.1, lead-acid battery technology is a modular “power” which can be used in the “seconds to minutes” range, but preferably is used as a “daily” storage system.

5.2.3.2 High Temperature Sodium-Based Batteries Sodium-nickel chloride (NaNiCl2, also called the ZEBRA battery) and sodiumsulphur (NaS) batteries are different compared with other battery technologies, due to the high operating temperature of around 300 C. These batteries use a solid-state electrolyte with sodium-ion conduction. The active masses are either liquid (sodium or sulphur) or solid with an additional liquid electrolyte (NiCl2). If the batteries cool down, an operation is no longer possible. The number of thermal cycles should stay as small as possible to avoid thermo-mechanical stress. To maintain the temperature it is necessary to compensate the heat losses. This can be achieved either by cycling the batteries, which generates heat due to the internal losses, or by heating the batteries. Typically, the temperature can be maintained quite easily if the battery runs one cycle a day. A commercial 16 kWh ZEBRA battery pack with thermal insulation has a heat loss of approximately 100 W. While the ZEBRA battery is used these days mainly for mobile applications, such as electric vehicles or busses, the NaS battery is used only in stationary applications. NaS batteries are the most promising technology for stationary large-scale battery storage systems. The cycle lifetime is in the range of 10,000 cycles and the specific costs for the materials are very low. Especially in Japan, several battery systems for grid support in the range of several MW and up to 50 MWh have been installed and are in operation. The main challenges are the solid-state electrolytes for Naþ-conductivity, the gaskets, overall battery management and safety issues. According to Table 5.1, NaS batteries are modular “daily” storage systems.

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5.2.3.3 Lithium-Ion Batteries Lithium-ion batteries have their origin in portable applications such as laptops, mobile phones or PDAs. Lithium-ion batteries have the highest energy density (more than 200 Wh/kg) among all rechargeable battery technologies and show also very high efficiencies in the range of 90–95%. These efficiencies are unique among all electrical energy storage systems in addition to electrochemical double-layer capacitors. Lithium-ion batteries also can achieve very high power densities. Lithium-ion battery technology is a manifold technology where many different material combinations are used. Various cathode and anode materials, as well as separators and electrolyte formulations, allow the creation of batteries with a wide range of performance characteristics with regards to energy density, power density, safety, cycle and calendar lifetime, as well as high or low temperature performance. The huge number of material combinations results also in a very dynamic development of new and improved battery systems. Many companies follow different material combinations. There is, as of yet, no favourite material combination or cell design for future lithium-ion technologies. Beyond the markets for portable applications and power tools, electro-mobility is the main driver behind the development of lithium-ion battery technology. Improvements in cell technology and economy of scale effects caused by the automotive market also support the introduction of lithium-ion batteries in stationary applications. A special focus is currently on the double use of the batteries from electric vehicles for driving and for grid support. Lithium-ion batteries show sufficient cycle lifetime to also work for load-levelling or other grid service applications, in addition to normal driving. The main challenges of the lithium-ion batteries are safety issues and costs. For the automotive sector, a price reduction for electric vehicle batteries down to approximately 200 €/kWh is estimated for mass production towards 2020. For stationary applications, costs can decrease by maybe another 20% or so due to lower requirements with regard to cooling or energy density. Lithium-ion batteries are especially competitive compared with lead-acid batteries for discharge times below 1 h. This is due to the fact that lithium-ion batteries can deliver almost 100% of their capacity even at high current rates, while lead-acid batteries can only deliver about one third of their capacity at high current rates. In Table 5.1, lithium-ion batteries are designated as a modular storage technology preferred for use for “power”, but also for “daily” storage systems. 5.2.3.4 Nickel Cadmium (NiCd) and Nickel-Metal-Hydride (NiMH) Batteries Like lead-acid batteries, NiCd battery technology is a traditional battery technology. NiCd batteries have a high mechanical robustness and achieve cycle lifetime in the range of several 1,000 full cycles. Furthermore, they have the best deep temperature performance of all rechargeable battery technologies. A downside is that NiCd batteries are significantly more expensive and have a lower efficiency compared with lead-acid batteries. Besides cost and efficiency concerns, the toxic cadmium contained in the batteries is a major obstacle for their further market penetration and use in stationary battery markets. Even though today one of the

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largest battery storage systems in operation in Alaska (40 MW peak, 6.5 MWh within a 15 min discharge) is made from NiCd battery cells, it is expected that this technology might be replaced by lithium-ion batteries in the coming two decades. NiMH batteries have been developed to replace the use of toxic cadmium. The resulting NiMH technology has a better energy density and better power performance. In the last decade, it has become the leading technology for hybrid electric vehicles. Several hundred thousand hybrid vehicles, especially from Japanese car manufacturers, are equipped with NiMH batteries. However, the basic material costs are high and therefore there are significant cost reductions that would be necessary for large-scale stationary applications. These would be hard to achieve. Therefore, NiMH will remain mainly a technology for mobile applications. According to Table 5.1, NiCd and NiMH batteries are primarily modular storage technologies or “power” storage systems.

5.2.3.5 Redox-Flow Batteries Redox-flow batteries are different from conventional batteries because their active materials are dissolved in the charged and the discharged state in a liquid solution. Typically these salts are diluted in a solvent, also called the electrolyte.1 The dissolved active materials are stored in tanks and are pumped continuously or on demand into a reaction unit where the electrochemical charge/discharge process takes place. The reaction unit itself consists of structures on which surfaces the reduction or oxidation of the dissolved ions takes place, with current collectors and a membrane as the electrolyte and separator. The general concept is quite similar to reversible fuels cells and therefore the technology is sometimes called the “liquid fuel cell”. The total charge/discharge efficiency of redox-flow batteries can be in the order of 75% and is, therefore, almost twice as high as for hydrogen storage systems. As the solubility of the ions in the solution is limited, the energy density of the most popular vanadium redox-flow battery systems is on the order of the lead-acid battery. However, their big advantage is that the energy capacity of such a battery can be scaled very easily by increasing the tanks, while the power rating of a redoxflow battery is scaled by the size of the stack. Thus, energy capacity and power rating can be scaled independently of each other. As mentioned before, vanadium is the most popular material for redox-flow batteries. As vanadium is stable in sulphuric acid as the solvent in four different oxidation states, it can be used for both electrodes. On the one electrode V2þ/V3þ is used, while the other electrode uses V4þ/V5þ. If the battery is fully charge, only V2þ and V5þ are present, in the fully discharged state it is V3þ and V4þ. The open

1

From a systematic point of view, the solvent is not the electrolyte (even though these terms are used frequently). The function of an electrolyte is to couple the electrodes of an electrochemical system as an ion conductor and at the same time as an insulator for electrons. In redox-flow batteries this is the membrane in the stack that separates the liquid active materials of the positive and the negative electrode.

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circuit voltage is about 1.2 V. Other interesting material combinations are, for example, Fe/Cr, Br2/Cr or NaBr þ Na2S4/Na2S2 þ NaBr3 (Regenesys). However, no mature products with materials other than vanadium are on the market. A major technical challenge so far is the permeability of the membrane for the active material ions. If the active materials mix, the battery loses its ability for storing electrical energy. Due to the fact that vanadium is used on both electrodes, this is not of major concern for the vanadium redox-flow battery. A problem for vanadium is that it is relatively expensive and therefore not an appropriate material to achieve the very low costs, which would be necessary to make the redox-flow battery more than a daily storage system. Cycle lifetimes in the order of 10,000 cycles have been demonstrated. This is the level that would be needed for practical purposes. Special focus must be put on the conventional part of the system, including the tank, the temperature control and the piping. Another problem is that leakages are quite common. More positively, recycling of the active materials of redox-flow batteries is quite simple and efficient. Zinc-bromine batteries are also listed as redox-flow batteries. But, even though the electrodes are also liquid in the charged state, this is not the case for both electrodes after discharging. Zinc is plated during discharging as metallic zinc in the electrode and therefore the stack can discharge only a limited amount of materials. After a certain capacity throughput, the stack is simply filled with zinc. An independent sizing of energy capacity and power rating is therefore not possible. This technology is not suited for discharge times of more than some hours and the zinc-bromine battery should therefore not really be seen as a member of the class of redox-flow batteries. In Table 5.1, redox-flow batteries are categorised as modular “daily” or – maybe in the future – “weekly to monthly” storage systems, if new material combinations are found.

5.2.3.6 Hydrogen Storage Systems Hydrogen for energy storage has two main characteristics: a low efficiency of 25–40% (electrical power to hydrogen to electrical power) and very low specific costs for storage capacity. The hydrogen is generated by electrolysers. Various technologies are available, working either at moderate temperatures around 60 C or in the range of 1,000 C, or which can be operated directly at higher pressure levels between 30 and 200 bar to avoid additional external mechanical compressors. The reconversion of hydrogen to electric power can be done either by fuel cells or hydrogen turbines. Storage systems in the range of several 100 MW will most likely have hydrogen turbines rather than fuel cells. The costs are lowest if caved salt caverns are used for storing hydrogen at pressures of 50–200 bar. Costs for caving salt caverns are in the order of 40 €/m3. They will inevitably vary for different locations, depending on the local geological conditions and depending on the distance to the sea for draining the salty water. Very low investment costs of less than 0.50 €/kWh (see equation below) can be achieved according to the following assumptions: hydrogen pressure in full charged conditions is 100 and 50 bar have to remain for the cushion gas (gas which

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must remain in the cavern to maintain a sufficient pressure), a thermal energy of hydrogen of 3.5 kWh/Nm3, and an efficiency of 50% for the conversion of hydrogen to electric power. Specific investment costs ¼

40 m€3 €ct ¼ 46 kWh kWh ð100bar  50bar Þ  50%  3:5 Nm3

(5.1)

Compared with electrochemical battery technologies with investments costs not below 100 €/kWh, the investment costs for hydrogen storage systems are very small. Therefore hydrogen is, aside from hydropower, the only storage technology that is suited for long-term storage. However, the economy of hydrogen systems depends mainly on the costs for the electric power during the charging process. Due to the low overall efficiency, at least 2.5 kWh electric power must be purchased for 1 kWh of delivered electric power. The business plans of such storage systems depend mainly on assumptions for the electric power price. Some people assume electric power costs to be zero in periods of excess energy from renewable energy systems, because variable costs tend towards zero. If very low electricity costs for charging the hydrogen storage systems can be achieved, this technology becomes very interesting. However, renewable energy systems have very high fixed costs and therefore the total revenues must be calculated for achieving an economic operation. The assumption of zero costs for excess power periods means that power must be sold at higher prices during other periods to assure the refinancing of the system. The technical potential for hydrogen storage systems is huge. The cavern of the diabatic compressed air energy storage of the Huntdorf plant in Germany with 300,000 m3 volume filled with hydrogen instead of compressed air results in a storage capacity at 100 bar of 26 GWh (assuming 50% conversion efficiency to electricity and 50 bar remaining gas pressure for maintaining sufficient pressure). The pumped hydropower plants in Germany together feature a capacity of about 40 GWh in total. This shows the huge capacity of even a single storage system. Current natural gas storage systems that are used in Germany for the national reserve have a capacity of 20 billion m3 in 44 storage systems. Using this storage capacity for hydrogen for electrical power results in 35 TWh of available electrical power. This is sufficient to supply the electric power consumption of Germany for approximately 21 days. According to Table 5.1, hydrogen storage systems are centralised “weekly to monthly” storage systems. Additional downstream technologies based on hydrogen production are also the synthesis of, for example, CH4 or methanol. Both require CO2, either from concentrated sources or from the air. This allows using the energy also as a gas or liquid fuel in other applications. Reconverting the fuels into electricity only makes sense in decentralised CHP units with additional heat usage. Otherwise, the additional losses from synthesising CH4 or methanol (efficiency is in the order of 80% , starting from hydrogen) just add to the total losses of the system. However, this could be a good option for serving the transport sector with fuels from renewable energies.

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Technical Description and Potential of “Electricity to Anything”

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Table 5.3 notes that CH4 or methanol from renewable hydrogen can be produced in modular or in centralised storage systems and can function as “electricity to anything” technologies, which can be used for “daily” or “weekly to monthly” storage systems.

5.3

Technical Description and Potential of “Electricity to Anything” Energy Storage Technologies for a Balanced Electrical Energy and Power Supply

Apart from the measures of using peak load power stations (thermal power stations) or storage options to balance the fluctuating feed-in from renewable energy sources, the demand side can also be influenced in the form of load management in order to contribute to balancing (Grimm 2007). The increased integration of fluctuating feed-in plants (wind, sun) by all means permits a change from demand-oriented power supply to a generation-oriented power supply. Strategies for generationoriented power supply and, thus, for influencing demand must be investigated and evaluated with regard to an equally possible central solution. Demand-side management (DSM) and demand response (DR) provide the potential to shift decentralised loads of end customers, such as private, commercial or industry customers, according to their requirements. An electronic marketplace, as developed in the framework of the German E-Energy projects, could serve the end customer here as the necessary communication and interaction platform for the marketing of its power flexibilities. The loads can be influenced by two different mechanisms in principle. On the one hand, the end customer can react manually to suitable incentives (e.g., price signals) (demand response). This concerns all electrical devices of the end customer. On the other hand, an automated load control is conceivable for such devices, the deferred use and modulated operation mode of which entail no loss of comfort, economic consequences or restrictions in everyday household/business life (dispensable loads) (demand-side management). Since the manual customer reaction of the first mechanism cannot be assessed at present,2 the analysis concentrates on the potentials of an automated load control. In the following, the industrial sector (which, as expected, has the highest potentials for load shifting), the future area of electrical mobility and the household sector (white goods (washing machines, dishwashers, tumble dryers), electromobile and heat pumps) are analysed with regard to a possible contribution for adjusting the load to the fluctuating feed-in. Suitable shiftable loads are identified and then evaluated. Moreover, a first estimation is given for the inclusion of the CHP plants with a maximum power of 10 MW in a demand-side management approach.

2 In the framework of the E-DeMa project, more detailed findings on this are expected, based on the experiences of a 9-month field test in 2012.

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DSM Industrial Sector

Klobasa (2007) examines the load management potentials of the electricity-intensive industry. Klobasa’s result was based on the following sectors for the provision of power flexibilities: cement industry, paper industry, cross-sectional technology (air-conditioning), nutrition (cold storage houses), basic chemicals, nonferrous metals and metal production. The maximum shiftable power is the maximum power that can be disconnected or connected in one moment in a branch of industry. A total load management potential of approximately 3 GW results for 1 day for all industries. This is an estimation for the whole of Germany; the regional and geographical concentration and distribution of individual industries’ load management potentials has not been considered. As special contract customers, most of the described potentials of the industry are already being used. Different terms of delivery and more differentiated tariffs apply for industry customers in principle, meaning power suppliers already recognise saving and power shifting potentials and negotiate contractual conditions with customers accordingly. It can therefore not be expected that the concentration of power suppliers on the industry sectors will strongly increase. Klobasa (2007) also indicates that the potentials in the industry will not decisively change in the coming years. These values are therefore assumed as constant for the years looked at: 2020, 2030 and 2040. The only exception is the aluminium industry. For this branch of industry, which is essentially equipped with high load shifting potential, observers of the industry assume that a large portion of the generation capacity will be moved abroad by 2020. The main reason for this is the high price for primary energy in Germany. Because of this, a decrease in the shifting potential by more than 70%, from the current approximately 0.3 GW to less than 0.1 GW, is assumed in this segment (Klobasa 2007). In conclusion, by necessity, this section was based on findings from a single reference; further detailed investigation is lacking. The estimation of the load management potential of industrial loads is an open topic for investigation and discussion.

5.3.2

Balance Provision by Electrical Mobility

The estimation of electric vehicles’ potential for the provision of balancing energy is derived from the analysis of the load profiles that would result in the case of an uninfluenced charging behaviour. These load profiles were drawn up from real passenger car movement patterns and are described in more detail in Rehtanz and Rolink (2009). Figure 5.1 represents the average load curve, standardised for a single passenger car on a working day with uninfluenced charging and a load power of 3.7 kW (Rehtanz and Rolink 2009). Depending on the charging infrastructure, different scenarios result. Either the vehicles are charged at home only (home) or also at work (home and work) or additionally in public places (wide-area).

Technical Description and Potential of “Electricity to Anything” Charging power in W/passenger car

5.3

Home

Home and Work

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Wide-area

500 450 400 350 300 250 200 150 100 50 0

Time of day h

Fig. 5.1 Daily load curves of electric vehicles

The following basic assumptions apply for all three scenarios. The day range per vehicle is limited to a maximum of 100 km. The battery storage of the vehicles is to be sufficient for the complete daily mobility requirement (on average, approximately 30 km). This precondition makes an almost free deferral of the charging possible during the day. The energy consumption of the vehicles is 20 kWh/100 km. Furthermore, it is assumed that the vehicles are only charged starting from a resting duration of a minimum of 1 h. This number is taken, because for shorter parking times, the effort of plugging in the car is too high. If this time is reduced to 15 min, there is only a little impact on the resulting curves. As can be seen in Fig. 5.1, the vehicles are largely charged in the morning at around 04:00 h in all three scenarios if the charging behaviour is uninfluenced. As can be seen from Fig. 5.1, a release (peak load) of up to 350–500 MW is possible with one million electrical vehicles for 1–2 h. This value varies, however, in the course of the day, and the condition at least has to be fulfilled that all vehicles are charged at a certain point in time, e.g., at 05:00 h in the morning. Since the charging times can be shifted over the course of a day, a further effect can be obtained for adjusting consumption to energy provision, although a consistent load management must be developed for this. Unlike conventional and large household loads (e.g., those of white goods), the power requirement of the electric vehicles rises in the course of the day.

5.3.3

DSM Household Sector

5.3.3.1 Technical Potential of DSM in the Household Sector In principle, an end customer is designated as a household customer. The Energy Industry Act (EnWG) defines an end customer as one who has an electricity consumption of less than 10,000 kWh/a.

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A demand-side management model is used for the calculations used in estimating the load shifting potentials in the household sector (Kreutz et al. 2010). The target function of the DSM model consists of smoothing the residual load curve described in Sect. 4.1.1.1 on a transport network level. This leads to the residual load, which still has to be covered with fossil power stations that can provide a smaller fluctuation range in the course of the day and hence, a smoother curve. For this, less (expensive) peak load power stations or storage systems have to be used. When selecting suitable electrical appliances in the household for an automated load control, two criteria must be fulfilled: – The appliance must have a sufficient annual energy consumption and a significant power consumption. – A shift in operation must be accepted by the end customer. For private and commercial customers, load control measures can be an issue. Possible acceptance of consumers must be considered. This applies in particular for the areas of lighting, TV/audio and cooking. Cooling and freezing appliances take up 19% of the average electricity consumption of a household, although these appliances only briefly require power when operating the compressor and have a very low consumption otherwise. Besides, the energy efficiency of these devices would be impaired by these measures. So-called white goods take up 15% of the electricity consumption in households. Shifting the operation of these loads is much easier to justify than with the groups of appliances described previously. Of course, the electricity requirement depends on the living and customary habits of the end customers. This depends on the numbers of washing machines, dishwashers and tumble dryers operated, the frequency of use and the program sequencing applied (Gaul 2009). In accordance with the investigations in Gaul (2009), a use probability distribution per day and a program sequence have been specified for the respective groups of white goods. No interruptions in the program sequence are envisaged in the simulation, since this would result in a reduction in energy efficiency. Shifting the load therefore means shifting the starting time of the washing, rinsing or drying program. In Table 5.5 the equipment, the frequency of the use and the electricity consumption for white goods are indicated. Since current studies (see Chap. 3) forecast a significant rise of heat pumps and these have a relatively high energy consumption, these consumers are also included in the calculations. Regarding acceptance, it is to be expected that the end customers have no objections to load management of personal heat pumps, as long as the Table 5.5 Assumptions for DSM – white goods (2020, 2030 and period 2040þ)a Equipment level [%] Use per day [%] Electricity consumption per program sequence [kWh] Washing machine 93 48 0.9 Tumble dryer 38 25 2.5 Dishwasher 62 40 0.7 a

No program interruption after starting

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103

consumer’s heat requirement is covered. For the modelling of the daily load curve, load profiles standardised to an energy consumption of 1,000 kWh/a are used, depending on the season. So while the heat pumps run 24 h a day in winter and in the transition periods as planned, they are only used during the day in summer, between 06:00 and 22:00 h. Following the current procedure of the distribution network operator with regard to heat pumps, demand-side management is simulated daily by up to three cut-off times of 2 h each for load reduction. As a boundary condition, it is taken into account that at least 2 h pass between two cut-off times. The following assumptions were set for heat pumps in the context of DSM: – Forecast of annual electricity consumption of all heat pumps in Germany: • 2020: 4.4 TWh (Nitsch and Wenzel 2009), • 2030: 6.1 TWh (Nitsch and Wenzel 2009), • 2040þ: 6.4 TWh, – Annual electricity consumption per heat pump: 6,000 kWh, – Maximum electrical power per heat pump: 2 kW. The electric vehicles to be integrated into the network in the future are also modelled as electrical consumers. As regards the number of electric vehicles, an increase from the one million electric vehicles required in 2020 to 20 million electric vehicles in the period 2040þ is assumed. It is assumed that the electric vehicles’ introduction to the market will be successful and that demand for them is high. For the estimation of the effect of DSM in the case of electric vehicles, the uninfluenced load curve, as well as the assumptions and considerations, were set, as described in more detail in Sect. 5.3.2. The two scenarios political RES and lead scenario (see Chap. 3) are taken as a basis for the model calculations. One average day and three extreme days are looked at for each of the years 2020, 2030 and 2040þ. It is assumed in the consideration that there are no time or capacity-related restrictions in the load shifting, i.e., that all electrical loads specified above are fully available at the time when they are to be shifted and the end customers show the highest flexibility and acceptance. The DSM is iterated. First, the cut-off times for the heat pumps are considered, since it is assumed that the end customer is not affected by the control measure. The resulting residual load then serves as a basis for the second step, the load shift of the electric vehicles. Finally, the white goods are shifted in order to fill the valleys of the residual load curve as far as possible, which the first two steps could not fill. Optimising prioritisation would be possible as part of advanced investigations. An exemplary representation for the starting situation of the DSM model, Fig. 5.2 shows the uninfluenced feed-in of renewable energy and the expected total load curve for Germany for the lead scenario 2040þ. The data above makes clear how high each controllable load group’s power demand ratio in each quarter of an hour is to the total load. The high number of renewable energy conversion plants in the case of the lead scenario for 2040þ is responsible for the fact that there are times in the course of the day where feed-in supply is above the load demand. Figure 5.3 shows the result of the DSM simulation for the lead scenario 2040þ. Compared with Fig. 5.2, the loads are moved into time slots where there is too much feed-in from renewable energy sources at the times where the load demand was

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80 70 60 Power [GW]

50 40 30 20 10 00:15 01:00 01:45 02:30 03:15 04:00 04:45 05:30 06:15 07:00 07:45 08:30 09:15 10:00 10:45 11:30 12:15 13:00 13:45 14:30 15:15 16:00 16:45 17:30 18:15 19:00 19:45 20:30 21:15 22:00 22:45 23:30

0

Time [h] Load without controllable appliances Electrical vehicles Feed-in

Heat pumps White goods

Fig. 5.2 Feed-in of renewable energy and load curve in Germany for lead scenario 2040þ without DSM 80 70

Power [GW]

60 50 40 30

20 10

00:15 01:00 01:45 02:30 03:15 04:00 04:45 05:30 06:15 07:00 07:45 08:30 09:15 10:00 10:45 11:30 12:15 13:00 13:45 14:30 15:15 16:00 16:45 17:30 18:15 19:00 19:45 20:30 21:15 22:00 22:45 23:30

0

Time [h] Load without controllable appliances Electrical vehicles Feed-in

Heat pumps White goods

Fig. 5.3 Feed-in of renewable energy and load curve in Germany for the lead scenario 2040þ with DSM

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Table 5.6 Maximum shifting potential of residual load for average days of political RES and lead scenario DPmax [GW] 2020 Lead scenario 3.0 Political RES scenario 3.0 2030 Lead scenario 4.3 Political RES scenario 5.0 2040þ Lead scenario 7.5

higher than the regenerative feed-in. This example also makes it clear that the load requirement of Germany is too small for the peak feed-in times, meaning that there are still times where storage systems have to be filled or additional energy exported. As a last resort, if the storage systems need to be filled and no export is possible, the power stations using renewable energy sources have to be shut down. In Table 5.6, the parameter DPmax describes the maximum, simultaneous lowering of the peak load for the two scenarios – political RES and lead scenario – for the years 2020, 2030 and 2040þ. The power use of heat pumps, electric vehicles and white goods, reaches its maximum at DPmax. The shifting potential DPmax will prospectively increase from 3 GW up to 7.5 GW in the scenario 2040þ due to the increasing use of heat pumps and electric vehicles from 2020 onwards. The calculation assumes a complete shiftability of loads in the course of a day; however, due to user restrictions in the course of a day it is to be assumed that the real usable potential is only about half as great. This difference can only be exploited if the DSM mechanisms, including down to individual devices, run smoothly in an automated and user-friendly manner. It has been shown that the DSM in the household sector can, on the assumptions made, contribute to a levelling of the energy balance on a transport network level during one day. Load shifts are only carried out here on a distribution network level. This makes it important to investigate the change in the degree of simultaneity due to the load shift in order to prevent an overload situation in the distribution network (see Sect. 6.1). Important secondary considerations in DSM are network capacities and the ability to ensure power supply. The expected economic effects of using DSM must also be looked at in detail (see Sect. 5.3.3.2).

5.3.3.2 Expected Economic Benefits from DSM in the Household Sector For the lead scenario in 2030 and 2040þ in particular, where the renewable feed-in exceeds the network load in some instances, it is determined, alongside the maximum shifting potential of the residual load (see Sect. 5.3.3.1), how large the energy quantity is which is shifted by the DSM at times where there is an energy oversupply. It is possible to indicate the proportion of feed-in of renewable energy that can additionally be used by DSM (“RES additional use”). This value refers to the total feed-in of renewable energy. This percentage proportion provides information related to the smaller feed-in of fossil power stations when using

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DSM. In order to determine the percentage change to the generation costs as well as to the CO2 emissions caused by DSM in the household sector, a model that determines the hourly employment of conventional power stations for 12 typical days of a year (working days, Saturdays and Sundays across four seasons) is used (see Waniek et al. 2008). Based on the consideration of the hourly load curve found within a “typical” day, power station restrictions, such as minimum operating and shutdown durations as well as the start-up costs resulting from this, can also be considered. The power station database on which the model is based includes all larger power stations installed in Germany today (approximately 370) and has been supplemented and adapted accordingly for future scenarios. Apart from the information on the type of fuel, year of construction and installed power, the network node of the network model used in Chap. 6 is also allocated to each power station. Thus, the simulation of the power station employment also provides the nodespecific feed-in and feed-outs necessary for the network calculations. The market model is based on the assumption that the marginal costs are the decisive influence on bidder behaviour. Peak pricing effects, i.e., strategic bidder behaviour in situations of shortage, are not taken into consideration. This means that the value of peak load plants is underestimated. However, since this in turn affects all technologies looked at, such as peak load power stations, storage systems or load management in equal manner, no significant fault occurs in the comparison of the technologies. Table 5.7 contains the results of the model calculations for the political RES and the lead scenario in the case where there are no underlying time or capacity restrictions for the load shifting (see Sect. 5.3.3). The following points can be stated as substantial trends: – In the lead scenario in 2030 and 2040þ in which a high amount of regenerative electricity cannot be consumed in the system, applying DSM allows for the additional use of 0.7% and 1.5% of the feed-in of renewable energy, respectively. These precise proportions do not have to be generated by the conventional power stations. – The generation costs can be reduced by DSM. The largest savings are approximately 14% in 2040þ. – Besides the positive effects, an increase in CO2 emissions is determined in the scenarios until 2040þ. The reason for this is that base load power stations are increasingly used when smoothing the residual load, which leads to increased Table 5.7 Parameters for the average days of the political RES and lead scenario for 2020, 2030 and 2040þ D generation DCO2 emission DPmax [GW] Additional use of RES [%] costs [%] [%] 2020 Lead scenario 3.0 – 2.4 3.4 Political RES scenario 3.0 – 1.1 0.2 2030 Lead scenario 4.3 0.7 2.7 4.4 Political RES scenario 5.0 – 0.1 1.3 2040þ Lead scenario 7.5 1.5 13.9 7.5

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CO2 emissions in the case of a power station mix with brown and hard coal. A CO2 reduction is obtained through the changed composition of the base load in the scenario 2040þ. The model calculations show that the DSM by all means carries advantages in the household sector, such as the contribution to levelling out the energy balance on a transport network level and cost savings. In order to conclude the analysis of the household sector shifting potentials during a day, the reduced generation costs are to be compared with the additional costs for implementing demand-side management across Germany in the household sector. The minimum requirement for the necessary infrastructure consists in transferring a control signal to a central place in the household based on the Institution of Load Management (aggregator), and then from there to the individual controllable devices. In principle, deriving a cost estimation requires differentiating between the outhouse infrastructure, which ensures transmission to the households, and the inhouse infrastructure. It is assumed that outhouse infrastructure will be available from 2020 onwards. The use of the power supply infrastructure (PLC) or the Internet is possible for this. The DSM does not entail marginal costs since existing systems can be used. Things are different with inhouse communication. A communication module (gateway) is necessary as a central reception point for the control signal, which prepares the signal if necessary and transfers it to the controllable devices via PLC or radio technology, for example. If this technology is not present in a household, additional costs are incurred by the additional inhouse communication infrastructure required. In the example scenario 2040þ, generation cost savings of approximately 13% can be made with the DSM. This corresponds to an annual amount of approximately 650 million €. If the highest equipment level of the controllable appliances (93% of households are equipped with washing machines, and some households with additional white goods, heat pumps and electric vehicles) is considered, 37.2 million households would be eligible for a DSM. Accordingly, macroeconomic savings of approximately 18 € per year result for an individual household. However, this value can turn out to be higher due to peak pricing in the market, which cannot be modelled here. The technical implementation, consisting of investments in the necessary infrastructure and ongoing expenditure for contract management, accounting system and further operating costs necessary for executing a DSM, should therefore not exceed this amount. The customer may have comfort losses due to the DSM, meaning that a high acceptance is only to be assumed in the case of complete automation. In conclusion, DSM mechanisms contribute to the balancing of demand that will be required in the future. The value of these mechanisms per household is very limited. If the estimated value of 18 € per year is compared to the electricity bill of an average household of around 1,000 € per year, of which around one-third is actual energy cost, it is obvious that a pure shift of consumption cannot create a value of around more than 10% and more likely of only 6% under this particular calculation. In the context of DSM and the management of electric vehicles,

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communication between all the devices and the management entity (aggregator) is of crucial importance. Only with a standardised information and communication system (ICT system) for all the devices that have to managed could such a management scheme be efficiently set up in the future.

5.3.4

Shutdown of Renewable Power Generation

According to the classification of technologies that can provide negative control power to the grid found in Table 5.3, the shutdown of renewable power generators is also a technical option. This is possible for seconds to minutes or even for daily needs. In contrast with fuel-fired power plants, renewable power generators have almost no savings in costs if they are turned down to provide negative control power. Therefore, the costs for a shutdown are equivalent to the generation costs and are dominated by the depreciation of the investment. Nevertheless, the costs are clearly predictable and the shutdown of renewable power generators is very fast. The costs for a kWh not fed into the grid are more or less equivalent to the rate paid to the system operator according to the renewable feed-in law. While PV generators can reduce their power output within milliseconds, it takes some 10 s for a wind turbine to come to a standstill. While regularly occurring events can be handled with storage systems, the shutdown of renewable power generators is especially an option for peak events. This option is essential from a technical, economic and legal point of view. Currently, wind turbines already have to reduce their power output if the grid is overloaded. There is no similar option when an imbalance in total power generation results in significantly negative prices at the power exchange. Generally, the negative prices at the power exchange should not exceed the value of the energy from renewable power generators determined by the renewable feed-in law. However, to implement such strategies, it would be necessary to develop appropriate procedures to determine the amount of energy that was not fed into the grid by the individual power generator. This is not a trivial exercise. It would most probably be necessary to use reference meteorological data for the region and an accepted technical characteristic for the power generation system to calculate the loss in energy generation.

5.3.5

Generation of Chemical Fuels such as Hydrogen, Methane or Methanol from Electricity

An increasing important topic of discussion is the use of chemical fuels as largescale storage systems that can be fed into different sectors of energy consumption. Basically all approaches to the generation of chemical fuels are based on the generation of hydrogen as a first step. Therefore, the general assumptions found in Sect. 5.2.3.6 on hydrogen production are valid here as well.

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Technical Description of “Anything to Electricity” Energy Storage Technologies

109

It is worthwhile to discuss the advantages of chemical fuels. The general idea is to use existing infrastructures for the storage and distribution of fuels, either as gas or as liquid fuel. The total consumption of such fuels is very high. To get to a CO2free energy supply will require a substitution of fossil fuels by CO2-neutral alternatives. Given that the potential storage capacity is huge, chemical fuels are an option that should be investigated. The technical processes to produce fuels from hydrogen (or using hydrogen directly) are well known. It is necessary to keep in mind that the processes typically have an efficiency of around 80% based on hydrogen as a raw material. This is true only if a concentrated source of CO2 is available, for example, from a conventional fossil fuel-fired power plant or from biomass power plants. If the CO2 is taken from the air, the total efficiency is reduced by a factor of approximately 0.8. For the following analysis, the availability of concentrated CO2 is assumed. The advantage of liquid fuels such as methanol from renewable energies is their very high energy density compared with all other electrical storage technologies. For renewable methane (CH4), there is the advantage of an existing infrastructure. Renewable methane can be distributed and used in the same way as natural gas. The main advantage of the concept is that production and usage of renewable fuels can be started without any additional infrastructural burden. Any size of production unit can be installed at any point in time to start the technology. Nevertheless, the overall efficiency of renewable fuels is low, especially if they are used to reproduce electricity. The efficiency from electricity to electricity is hardly more than 30%. Therefore, renewable fuels should be generated only if all options for distributing the generated electric power via grids are used and if a pure hydrogen storage system with reconversion of hydrogen to electricity on site makes no practical sense. Renewable fuels are, in addition to hydrogen and very large pumped hydro storage systems, one of the only options for monthly storage systems.

5.4

Technical Description of “Anything to Electricity” Energy Storage Technologies for a Balanced Electrical Energy and Power Supply

5.4.1

CHP Plants with Thermal Storage

The rising number of decentralised combined heat and power plants (CHP plants) offers the possibility of aggregating power from decentralised generation. Two different types of CHP plants are focused on: The m-CHP plants with an electrical power generation of up to 10 kW and the local heat CHP plants for heating centres in combination with a local heat network with a maximum electrical power generation of 10 MW. The following assumptions and conditions form the basis for determining the shifting potentials: – The m-CHP plants looked at are run in monovalent operation and cannot be modulated but are subject to a clocking (connection and disconnection).

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– The local heat CHP plants are run in modulated operation. In order to cover the increased heat requirement a peak load boiler is additionally used. This peak load boiler is able to monovalently supply the adjacent local heat network with heat energy (if the CHP plant is being maintained or repaired). – All plants are heat-controlled and the heat requirement of the end customer must be covered at all times. – All plants have a sufficiently dimensioned heat store. – With both plant types, the associated heat store is completely filled in 4 h in full load operation and is also emptied in 4 h in the case of a high heat requirement. – Due to the varying heat requirements over the course of a year, the results after the summer and winter seasons are differentiated. – All plants can be coordinated centrally. The shifting potentials of the plant types are determined separately and at first, on a pro rata basis, based on installed power. In addition, positive and negative shifting potential are differentiated. The positive shifting potential represents the amount by which the generation power can be increased. The negative shifting potential indicates the amount by which the generation power can be reduced. Finally, forecasts from studies are taken as a basis and used to determine future shifting potentials. When stochastic mixing and clocking are taken as a basis, approximately 50% of the total installed power of all m-CHP plants is available on a winter day. This means that approximately 50% of the m-CHP plants are always in operation. Since the heat requirement is only given by hot water preparation in summer and since the m-CHP plants are thus only rarely in operation during the day, a power portion of 5% of the installed power of all m-CHP plants without coordination is assumed. If there is central coordination, a power percentage of 100% of the installed power of all m-CHP plants is available for 4 h maximum on one winter and one summer day. With coordination in a negative direction it is also possible to lower the power of all m-CHP plants to zero on a winter and a summer day. A positive and negative power potential of 50% of the installed power of all m-CHP plants results for one winter day. There is a very small power potential in a negative direction for a summer day, since the majority of the plants are not in operation at the same time (approximately 5%). With an appropriate coordination, the positive shifting potential amounts to 95% of the installed power of all m-CHP plants. In both cases however, the time sequence for filling and emptying the store is to be considered. When using the local heat CHP plants, it is necessary to determine, in a similar way to the m-CHP plants, how high the proportion of the generation power of the local heat CHP plants is in relation to the installed power of all local heat CHP plants without coordination. According to the dimensioning of the heating centre, the local heat CHP plants run continuously in winter without coordination and in full load operation. They are not subject to any clocking and are dimensioned in such a way that they cover the basic heat requirement of the relevant area. There is therefore no positive power potential in winter.

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Technical Description of “Anything to Electricity” Energy Storage Technologies

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In a similar way to the m-CHP plants, it is possible to set the generation of the local heat CHP plants to zero through coordination. There is a negative shifting potential of 100% of the total installed power of the local heat CHP plants in winter. It should be noted that this power can be available for a very long time, since the heat requirement is covered by an appropriate peak load boiler. It is nevertheless of interest to put the local heat CHP plant back into operation as soon as possible for reasons of economic efficiency. In summer, the local heat CHP plants are not in operation due to the low heat requirement. This means there is no negative shifting potential. It is however possible for all local heat CHP plants to feed in at the same time by way of coordination. Thus, there is a positive shifting potential of 100% of the total installed power of the local heat CHP plants. This power can only be provided for 4 h, since the heat store is filled after 4 h. In accordance with Nitsch (2008), the gross electricity generation of the m-CHP and local heat CHP plants is 30 TWh in 2020 and about 41 TWh in 2040. A high use of biogas is to be assumed here. A rise to 45.5 TWh is assumed for 2040. In 2020, a total power from the decentralised CHP plants of 11 GW is assumed. The percentage rise of the gross electricity generation has been used as a basis for determining the installed power of 2030 and 2040. An installed power of 15 GW results for 2030 and of 17 GW for 2040þ. However, these numbers strongly depend on the development of the building insulation, which has a high impact on the heat demand and on the heat-electricity ratio of the technology used. In Table 5.8, the forecast gross electricity generation and installed power of m-CHP plants and local heat CHP plants in Germany for 2020, 2030 and 2040þ is represented. It is to be noted here that the gross electricity generation in 2020 and the associated installed power from Nitsch (2008) suggest a very low average number of operation hours for the CHP plants. Based on these values, it is assumed that the number of operation hours of the local heat CHP plants is twice as large as that of the m-CHP plants. Accordingly, the power values Pm and Plocal heat shown in the table result. In the following tables, the shiftable power of the CHP plants in Germany determined above is presented. In Table 5.9, the amount by which generation power can be increased is indicated. This positive shifting potential is accompanied by the negative shifting potential, shown in Table 5.10. The negative shifting Table 5.8 Forecast gross electricity generation and installed power from CHP (<10 MW) (Nitsch 2008)

2020 2030 2040þ a

Gross electricity generation CHP plants [TWh] m CHP Local heat CHP Wm/TWh Wlocal heat/TWh 11.0 19.0 16.0 25.0 18.0 27.5

Total Wges/TWh 30.0 41.0 45.5

Installed power CHP plants (GW) m CHP Local heat CHP Pm/GW Plocal heat/GW 5.0a 6.0a 6.5a 8.5a a 10.0 7.0a

Total Pges/GW 11.0 15.0a 17.0a

This value is based on calculations, which in turn are based on the values from Nitsch (2008)

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Table 5.9 Positive shifting potential of the CHP plants (<10 MW)

2020 2030 2040þ

Shifting potential m CHP [GW] Winter Summer 3.0 5.7 4.25 8.1 5.0 9.5

Shifting potential Local heat CHP [GW] Winter Summer 0 5.0 0 6.5 0 7.0

Shifting potential m and local heat CHP [GW] Winter Summer 3.0 10.7 4.3 14.6 5.0 16.5

Table 5.10 Negative shifting potential of the CHP plants (<10 MW)

2020 2030 2040þ

Shifting potential m CHP [GW] Winter Summer 3.0 0.3 4.25 0.4 5 0.5

Shifting potential Local heat CHP [GW] Winter Summer 5 0 6.5 0 7 0

Shifting potential m and local heat CHP [GW] Winter Summer 8.0 0.3 10.75 0.4 12 0.5

potential represents the amount power by which the generation power can be reduced. Both a winter and a summer day are shown. The results indicate that only the m-CHP plants can realise a positive shifting potential in winter. Since local heat CHP plants are in continuous operation in winter without coordination, there is no positive shifting potential during this time. As the plants are only very rarely in operation in summer, a very high positive shifting potential can be reached on a summer day. Positive shifting potentials of 10.7, 14.6 and 16.5 GW are obtained in summer. Since the load peaks are observed in winter, however, coverage gaps in generation will more likely arise during the winter months. Looking at Table 5.10, it becomes clear that there is a very large negative shifting potential in winter. In 2020 to 2040þ, the total negative shifting potential rises from 8.0 to 12 GW. By contrast, a very small negative shifting potential is hit because of the low heat requirement in summer. The maximum value of the shifting potential in summer is 0.5 GW in the period 2040þ. As a concluding remark, it should be noted that in estimating maximum potential only winter and summer days were examined in this chapter. The transition periods offer possibilities for striking balances between positive and negative shifting potential. This means that a similar power value can be shifted both positively and negatively. It should be stressed that the shifting potentials for the different years are hypothetical. The development of the CHP plants beyond 2020 is difficult to estimate, since the CHP plants up to an electrical power of 50 kW are currently only in the market introduction phase.

5.5

Conclusions on Options for Demand Response and Demand-Side Management

5.4.2

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Conventional Power Plants Using Fossil, Nuclear, Hydro or Biofuels

According to Table 5.2, positive control energy can be supplied to the grid also from conventional power plants. In fact, today the primary control power comes almost completely from conventional power plants and through 24-h forward planning.

5.5

Conclusions on Options for Demand Response and Demand-Side Management

The power shifting potential of customer loads and distributed generation was estimated in the previous sections. Its management includes demand response, demand-side management and virtual power plants, which enable the shifting of distributed generation and load on a daily basis. Storage technologies that are applicable come from several classes of storage systems. Therefore, a separate analysis of all options is carried out in this section. In order to compare and evaluate the sectors examined in Sects. 5.3.1–5.4.1, the most important parameters are summarised in Table 5.11. As regards the maximum shifting potential, it should be noted again that this really represents a maximum value, which is reached in the case of an above-average user acceptance. The values and evaluation in the table refer to the lead scenario 2040þ, and thus to the period in which the new technologies will most probably be established and spread on the market. Looking at Table 5.11, it becomes clear that implementing DSM offers the largest potential with CHP plants. With a positive shifting potential of 5 GW in winter and 16.5 GW in summer, and a negative shifting potential of 12 GW in winter, the maximum positive shifting potential is far above the potential of controllable devices. However, due to the load correlation, the winter value is more relevant as the CHP is used fully during cooling periods. On the assumption that the number of electric vehicles will rise exponentially in the coming years and that the shifting potential across Germany will become very large because of this, it is important to include this sector in DSM. User acceptance Table 5.11 Prioritisation of the individual sectors for the scenario 2040þ Maximum shifting potential [GW] Heat pumps 0.6 White goods 1.9 Electric vehicles 6.0 Industrial loads 2.8 CHP (<10 MW) þ5/12 (winter) þ16.5/0.5 (summer)

User acceptance Very high Low High Very high High

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for electric vehicles is high as long as the car is not used. It is assumed, however, that the users do not want to be restricted in their driving behaviour. The heat pumps will have a relatively small potential of 0.6 GW in future. Due to very high user acceptance, including heat pumps in DSM systems is seen as more important than including white goods. White goods have a large shifting potential of 1.9 GW, but low user acceptance is assumed. White goods represent the greatest influence on user behaviour, and therefore it is assumed that they will be accepted by users only to a very limited extent. Due to restrictions in use and problems of acceptance, only half the potential that is technically possible is likely to be available in reality for electric vehicles and white goods. Since DSM already exists to some extent for industrial loads with a potential of 2.8 GW, it is necessary to ensure that this DSM continues to be improved and that newly developed generation processes can be added if necessary. User acceptance exists thanks to relatively large financial incentives. In total, the load shifting potential within a day is technically between 16.3 and 23.3 GW, but in real terms, considering user acceptance, probably less than 10 GW. A coverage contribution to the power gap of up to 35 GW in the scenario 2040þ must therefore be considered as a necessary option for future power system scenarios.

5.6

Life Cycle Cost Analysis of Storage Technologies

Several storage technologies have been discussed, however, based on the given information it is almost impossible to choose “the best” technology. Several parameters define the performance of a storage technology and they are very different in nature and therefore difficult to rate against each other. The following table shows and describes the parameters that need to be defined for each storage technology. The parameters need to be adjusted to each other. For instance, for a high-quality device, high cost and long lifetimes can be an optimum choice, but a low-cost version with short lifetime might also be suitable. In fact, even more parameters must be taken into account for the cost calculation, such as costs for purchasing land, a building for the system or the suitable temperature range. These costs are not taken into account here, because they are either extremely site dependent (land) or will appear more or less in the same way for all technologies (building). For stationary applications, the temperature is typically not that important because the storage systems are operated under well-controlled conditions. Other aspects such as recyclability or limitation of resources are important parameters for judging the suitability of a storage technology. They are discussed in Sect. 5.7. However, they are of minor importance for an individual business decision if a new storage system is planned. However, a comparison of technologies can be made only if the application itself is well defined and the optimum parameters and options for a specific storage

5.6

Life Cycle Cost Analysis of Storage Technologies

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Table 5.12 Parameters defining a storage technology Parameter Unit Description Costs per installed capacity €/kWh Defined per kWh of total installed capacity (independent from the net usage of the storage system) Calendar lifetime of Years Lifetime until the storage system itself needs storage system replacement Costs per installed power €/kW Includes all costs attributed to power related devices, such as inverters or generators The costs for the components needed during charging and during discharging can be different Calendar lifetime of Years Lifetime until the power-related elements need power-related components replacement The lifetime for the components needed during charging and during discharging can be different Efficiency % Three different efficiency values must be distinguished: – Charging efficiency (grid to storage) – Storage efficiency (possible losses in the storage, e.g., for gas compression) – Discharging efficiency (storage to grid) All are defined as the ratio of energy coming out of the process to energy going into the process. All auxiliary consumers are included Self-discharge %/month Energy losses related to the installed storage capacity while the energy is stored Depth of discharge (DOD) % Percentage of used capacity in day-to-day operation # Number of cycles at the defined DOD that can be Cycle lifetime of the storage system achieved in a constant cycling mode Maintenance and repair %/year Costs related to the total investment costs for keeping costs the system in perfect condition. Does not include the replacement costs for a component at the end of its lifetime

technology according to Table 5.12 are chosen. Storage applications need to be defined by the parameters listed in Table 5.13. Taking all these aspects into account, a first order approximation makes it possible to calculate the costs of the storage system expressed as €ct/kWh for power fed into the grid from the storage system. The calculated value is the amount of money that must be earned while selling power to the grid. It does not include the cost of buying the energy that can be sold to the grid. Based on this methodology, it is possible to compare the different storage technologies along all relevant aspects. Low efficiency, for example, is taken into account through the costs for buying the energy that is needed for the losses. Lifetimes of storage technologies are also taken into account. The methodology has not been developed to find out whether the storage system can be operated on an economical basis. This would require analysing not only costs but also the possible income that can be achieved with the system. For a given system definition, according to Table 5.13, the earnings should be independent from

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Table 5.13 Parameters defining a storage application Parameter Unit Description Charging power kW Defines the required power at which the storage systems can be charged Discharging power kW Defines the required power at which the storage system can be discharged Available energy from kWh Defines how much energy can be supplied from the storage the storage system system to an application Cycles per day #/day Defines how often per day the available energy from the storage system will be discharged (used) System lifetime Years Required period for which the storage system should be operated Capital costs % Capital cost rate used for the annuity calculation: the difference between the expected capital return rate and the inflation rate Electricity costs €ct/kWh Average rate at which the storage system buys electricity. The electricity costs are needed to calculate the operational costs of the storage systems, namely the energy which is getting lost in the efficiency chain of the system Table 5.14 Reference cases for an economic comparison of different storage technologies Reference case Long-term storage (“weekly to monthly storage”)

Short description

Energy storage for long periods with almost no wind energy (200 h operation at full power in both directions) Load levelling in Typical design of existing the transport grid large-scale pumped hydropower (“daily storage”) stations (e.g., Goldisthal) Peak shaving in the Storage system for peak shaving LV grid (“daily and load levelling storage”)

Charging power ¼ discharging power

Available energy

Cycles per day

500 MW

100 GWh

0.06 (1.5 cycles per month)

1 GW

8 GWh

1

100 kW

250 kWh

2

the specific storage technology. The methodology is mainly developed to compare storage technologies from the classes “daily storage” and “weekly to monthly storage” according to Sect. 5.1. Such a comparison of storage technologies has been performed in the framework of the VDE/ETG study (B€ unger et al. 2009). Some exemplary results from this study are discussed in the following paragraphs. Three different reference cases according to Table 5.14 will be discussed. Only some preselected technologies are analysed for the different reference cases. The width of the bars in the graphs (Figs. 5.4, 5.5, 5.6) represents the expected cost reduction potential starting at today’s costs and ending where specialists expect the costs to be in about 10 years’ time, assuming a very strong market growth. The data basis comes from literature studies and expert knowledge. The cost reduction potential is based on existing and demonstrated technologies and does not assume

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Hydrogen > 10 years

today

CAES today

> 10 years Pumped Hydro

depending on location 0

20

10

30

40

Fig. 5.4 Comparison of life cycle costs per delivered kWh for the reference case “long-term storage” (system lifetime 40 years, capital costs 8%, electricity costs 4 €ct/kWh)

Hydrogen today

> 10 years today CAES

> 10 years

Pumped Hydro

depending on location 0

5

10

15

20

25

costs [ ct/kWh]

Fig. 5.5 Comparison of life cycle costs per delivered kWh for the reference case “load levelling in the transport grid” (system lifetime 40 years, capital costs 8%, electricity costs 4 €ct/kWh)

totally new developments. For the established technologies, the bandwidth is smaller than for those technologies that just come onto the market. Finally, the left-hand end of the bar represents the costs that could be achieved assuming sound technological development and taking into account economy-of-scale effects. For the reference case “long-term storage”, only pumped hydro storage systems reveal relatively low costs (Fig. 5.4). Unfortunately, there is no clear vision as to where such huge pumped hydro system could be installed. Therefore, hydrogen storage technology with underground caverns is the most realistic option. Compressed air storage systems are not suited for this application due to high specific costs for the storage media. The reference case “load levelling in transport grids” represents the class of large existing pumped hydropower stations, such as Vianden and Goldisthal. The results show that adiabatic compressed air storage systems are comparable from the cost point of view. However, the impact of compressed air storage systems on the

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5 to 10 years

today

Redox-flow (Vanadium) NaNiCl (Zebra, high temp.) NaS (high temp.) Lithium-ion NiCd Lead-acid 0

5

10

15

20

25

30

Fig. 5.6 Comparison of life cycle costs per delivered kWh for the reference case “peak shaving in the LV grid” (system lifetime 20 years, capital costs 8%, electricity costs 5 €ct/kWh)

environment is significantly less compared with new artificial lakes for the pumped hydro systems. Hydrogen storage systems are competitive for daily storage systems due to their low efficiency. However, this result depends very much on the assumed costs for the electricity that would need to be purchased to compensate the efficiency losses. Calculations not shown here indicate that battery technologies have a medium to long-term potential of 8–12 €ct/kWh. Such battery systems must be designed in a highly modular way from several smaller units. However, the costs are approximately twice as high as for the pumped-hydro storage systems. For the reference case “peak shaving in the LV grid”, all the different battery technologies can generally serve the requirements. The results show that the NaS battery technology has the best potential in terms of costs, followed by the lead-acid batteries. Zinc-bromine and vanadium redox-flow batteries can come close, but they are several years behind in status with regard to technical developments and the available field experience. Because the specification asks for two cycles per day, the specific costs are at best in the range of 5 €ct/kWh. To analyse the impact of the chosen parameters on the results, a sensitivity analysis has been performed. The results are shown here only qualitatively to get an idea of which parameters to keep an eye on (Table 5.15). The analysis is focused on the storage system classes “modular storage for grid use only” and “centralised storage systems” which are at the same time also part of the “electricity to electricity” class. A generalised analysis of the “modular storage with double use” technologies is very difficult because the costs depend too much on their main application.

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Table 5.15 Qualitative results from the sensitivity analysis for two different reference cases and technologies Reference case “peak shaving Parameter Reference case “load levelling in in the LV grid”, technology the transport grid”, technology “lead-acid battery” “pumped hydro” Efficiency Low to medium Low Electricity costs Medium to high Medium Costs per installed High High capacity Number of cycles High High per day Capital costs Medium Low Self discharge Not analysed Very low Maintenance and Not analysed Very low repair costs

In addition to the previously discussed issues, a cost analysis reveals some important general findings: – Most storage technologies have high initial investment costs and low operational costs. Only those storage technologies with relatively short lifetimes or low efficiencies have significant costs during their lifetimes. Therefore, capital costs are very sensitive to life cycle costs. This is comparable in the case of power production from renewable energies, such as wind and PV generators. – Battery technologies with a cycle lifetime but also high investment costs can hardly compete with battery technologies with shorter lifetimes and lower investment costs. As an example, doubling the lifetime of a storage technology from 10 to 20 years at a capital cost rate of 8% is only economical if the investment costs do not increase by more than 44%. – Among the pure storage systems for the long-term storage task, only hydrogen storage systems and pumped-hydro systems have a chance. However, in Germany there is very little potential for pumped hydro technology. Hydrogen storage systems are attractive despite the low efficiency if underground salt caverns are used for storage. – It is interesting to see that the cost projections for the coming years for most of the battery storage technologies are somewhere in the range of 5–10 €ct/kWh for a scenario of 2 cycles per day. This shows that it is worthwhile to follow the development of several different battery technologies and to see which of the technologies can ultimately meet the expectations.

5.7

Assessment of Future Viability of the Technologies’ Environmental Issues, Resource Use and System Characteristics

A major question related to auxiliary technologies for the generation and distribution of electrical energy, such as energy storage and electrical networks, is their viability in a future energy system. The main aim here is to consider whether

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aspects that are relevant for a long-term viable usage of the energy system could hamper the application of auxiliary technologies in the future. First, the methodology and data used for the quantitative assessment is explained. Then environmental impacts, resource use and system characteristics are analysed. A conclusion discusses the results of the analyses.

5.7.1

Methodology and Data Applied for Quantitative Assessment

The basis for evaluating technologies, particularly in relation to their environmental and resource suitability, is life cycle calculations. The technologies in focus are auxiliary energy storage technologies. It is beyond the scope of this study to carry out complete life cycle assessments of all auxiliary technologies, including energy storage systems and upgrades and extensions of electricity networks. Instead, published life cycle assessments are reviewed and analysed. In addition to journal articles and reports, data from the widely applied ecoinvent database (version 2.2, Ecoinvent 2010) are considered and used with the SimaPro life cycle assessment software. Based on this dataset, a life cycle screening of the technologies is made applying life cycle data on background processes and on the energy system for 2050 generated in the integrated project NEEDS3 (European Commission 2008b; ESU and IFEU 2008) (see also Sect. 3.1.3). The background processes projected to 2050, which for the study were individually implemented into the ecoinvent database, include production processes for aluminium, copper, nickel, iron, steel, metallurgical grade (MG)-silicon, zinc, clinker and flat glass as well as the electricity mix of UCTE countries and aluminium production. Details are described in ESU and IFEU (2008). For the impact analysis made by this study, when no sound estimates are available relating to future technological developments, it is assumed that current technologies remain unchanged into the future. Where sound estimates for future developments are available, these are taken into consideration.

5.7.2

Environmental Impacts

5.7.2.1 Assessment Methodology and Assumptions In order to evaluate the technology options with respect to their environmental impacts, an analysis of impacts and, where possible, related external costs is carried out. The estimated values of external costs can be considered in addition to the pure market-reflected costs for system optimisation purposes. Two types of technologies are investigated in the analysis: storage technologies and electrical networks. In order to make the results for the technologies comparable, the following functional units have been applied:

3 “New Energy Externalities Development for Sustainability” – intergrated project funded by the European Commission in the sixth framework programme.

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– For storage technologies: kWh electric energy provided over the entire lifetime, – For distribution and transmission lines: an elementary unit of 1 m installed power line. For the environmental impact assessment, two methodologies where followed. The first is the so-called impact pathway approach developed within the ExternE project series. Starting from emissions of substances, concentration increases are estimated. These are used in exposure-response functions derived from epidemiological studies to assess individual impacts, which finally are evaluated as far as possible to arrive at external cost values. The impact pathway assessment has the advantage that the effects can be attributed to sources. The evaluation of diverse effects can be very impact specific. For instance, human health effects are distinguished with respect to individual diseases, with the applied monetary values considering as far as possible the direct individual loss of utility due to pain, suffering and time lost (see, e.g., Hunt and Markandya 2001). These are ideally deduced from willingness-to-pay studies as well as the indirect economic effects of production losses and health expenditures. The diseases and monetary valuation for human health impacts used in the calculations are shown in Table 5.16. As data from life cycle screening are used for the estimations and thus the relevant emissions are distributed over Europe, damage factors, which have been averaged over the geographical areas and height of emission from Preiss et al. (2008), were applied. The factors have been assessed on the basis of detailed runs of the EMEP model, “a multi-layer atmospheric dispersion model for simulating the long-range transport of air pollution” (Tarraso´n 2009, p. 3) with a horizontal resolution of 50  50 km2 (see ibid.), and detailed data of the analysed receptors, assuming the current geographical distribution together with respective exposure response functions and specific monetary values (see Preiss et al. 2008). Thus, impacts on human health, crop losses, material damages of facades and loss of biodiversity are covered. Details on the effects covered in the remaining impact categories and on the explicit monetary values used can be found in (ibid.). In order to show the influence that variations of the most controversially discussed evaluation, i.e., the valuation of years of life lost due to chronic exposure by particles, may have, upper and lower bounds of 100,000 and 25,000 € per year of life lost, as recommended by Desaigues et al. (2006), are applied for the sensitivity analysis. For the evaluation of climate change effects, the medium value of 70 €/tCO2,equivalent,4 recommended by the German Environment Agency in its methodological convention on external costs assessments, was applied (Umweltbundesamt 2007). The value represents a “best guess” on marginal damage costs derived from assessments carried out by Downing et al. (2005) with the so-called FUND model and has been recommended by Krewitt

4

If not differently indicated, the base year 2000 is used for the evaluation of environmental effects.

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Table 5.16 Human health effects and their evaluation as example for the approach applied in the study Risk group Physical impact Specific Specific monetary [1/(mg/m3)] impact unit value [€/impact unit] Primary and secondary inorganic aerosols <2.5 mm All 6.51E-04 YOLLa Life expectancy 40,000 reduction – chronic effects Net restricted activity All 9.59E-03 Days 130 days Work loss days All 1.39E-02 Days 295 Minor restricted activity All 3.69E-02 Days 38 days Primary and secondary inorganic aerosols <10 mm Increased mortality risk Infants 6.84E-08 Cases 3,000,000 (infants) New cases of chronic All 1.86E-05 Cases 200,000 bronchitis Respiratory hospital All 7.03E-06 Cases 2,000 admissions Cardiac hospital All 4.34E-06 Cases 2,000 admissions Medication use/ Children 4.03E-04 Cases 1 bronchodilator use Medication use/ Asthmatics 3.27E-03 Cases 1 bronchodilator use Lower respiratory Symptomatic 3.24E-02 Days 38 symptoms (adult) adults Lower respiratory All 2.08E-02 Days 38 symptoms (child) Ozone [mg/m3] (based on sum over means over 35 ppb) Increased mortality risk All 2.23E-06 YOLL 60,000 Respiratory hospital All 1.98E-06 Cases 2,000 admissions Minor restricted activity All 7.36E-03 Days 38 days Medication use/ Asthmatics 2.62E-03 Cases 1 bronchodilator use Lower resp. sympt. All 1.79E-03 Days 38 excluding cough Cough days All 1.04E-02 Days 38 Source: Preiss et al. (2008) YOLL: years of life lost

a

and Schlomann (2006). For sensitivity analysis, values of 20 and 280 €/tCO2 have been recommended (Umweltbundesamt 2007). The substances considered for the analysis comprise the classical air pollutants SO2, NH3, NMVOC, NOX

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and primary particles, as well as greenhouse gases, toxic substances and radionuclides. As a second approach, in order to cover further impacts, a widely applied standard method of Life Cycle Impact Assessment “CML 2001” is used. The effects are analysed in detail so that individual aspects of relevant technologies can be discussed. Using this methodology, a large variety of impact categories can be covered: abiotic depletion, acidification, eutrophication, global warming, ozone layer depletion, human toxicity, fresh water aquatic ecotoxicity, marine aquatic toxicity, terrestrial ecotoxicity and photochemical oxidation. In each category a substance is selected which is used as a reference. The potential effects of other substances are then estimated relative to this reference substance. On this basis, factors are derived which make it possible to express the potential effects of all substances in each category in terms of equivalents of the reference substance. Thus, the potential impacts of all substances can be aggregated by category, assuming implicitly average conditions. According to the baseline assumptions in the CML 2001 method, the following time horizons are used: 100 years for the global warming potential (GWP100) and infinite time horizon for the toxicity effects. For ozone layer depletion, steady state has been assumed. The results for the individual impact categories are not further aggregated.

5.7.2.2 Environmental External Costs of Balancing Technologies Figure 5.7 shows the external costs, assessed by following the impact pathway approach for storage technologies and alternative technologies with the data from ecoinvent 2.2 extended by data assumed for the future energy system within the NEEDS project (Ecoinvent 2010; NEEDS 2010). Assumptions for the cycle life of the batteries used were 3,000 for NiMH and 4,500 for Li-Ion batteries and for the gravimetric energy density 80 and 200 Wh/kg, respectively. Assuming the results of life cycle assessment from Rydh (1999), the numbers for lead-acid batteries include the processes of production of secondary (99%) and primary lead (1%) (26.8 g lead/ kWhel) and sulphuric acid (4.2 g sulphuric acid/kWhel). As no complete data for hydrogen storage is available, data from the assessment of hydrogen electrolysis for a hydrogen fuel station are taken from NEEDS (Maack 2008). The values assessed represent costs occurring due to emissions in 2050.5 From the results, it becomes obvious that emissions of SO2 will prospectively lead to the largest effects caused by using energy storage units. These are, for example, in the case of the NiMH battery6 and the electrolyser generated by high direct SO2 emissions in the nickel production process. As lead-acid and lithium-ion batteries are much more relevant for energy balancing and the results for NiMH are so high, the bar has only been displayed up to 10 € per MWel provided. Although 5

In order to project costs from today to 2050, the growth rate of GDP is assumed to be 2% until 2030 and 1% thereafter, with an income elasticity of 0.85. 6 As no other data are available, for the NiMH battery a dataset for 1 kg of notebook batteries is taken from ecoinvent 2.2.

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10 NH3, toxics & radionuclides

16

40

31

9.3

NMVOC

9

NOX

Euro/MWhel provided

8

primary particles

7.1

7

SO2 CO2

6 5 4 3 2 1.0

1.3

1.0

0.77

1

0.51

0.38

0.38

gas CC-CCS 500MW

wind offshore

photovoltaics high effects (multi-crystalline silicon, Central Europe)

photovoltaics low effects (cadmium telluride, Southern Europe)

hydrogen storage - only Electrolyser

pumped hydro non -alpine

pumped hydro alpine

Lithium- ion battery

Lead-acid battery

Nickel-metal hydride battery

0

Fig. 5.7 External costs in 2050 of analysed storage technologies, considering only their construction, and a photovoltaic facility, a wind power plant, and a gas combined cycle plant with CCS, considering the whole life cycle, in € per MWh provided. (The values for the storage facilities do not include the operation phase so that the electricity loss due to storage is not considered in the estimates. However, this can easily be calculated from the values by assuming a certain technology for electricity production. Using electricity from wind offshore plants assessed here and an efficiency of the storage option of 80% would result for example in additional external costs of 0.51 * 0.2  0.1 € per MWhel. For the assessment of nickel-metal hydride batteries, the ecoinvent unit process for batteries in notebooks is taken. For lead-acid batteries, only the processes of providing lead and sulphuric acid are considered according to the material required per kWhel taken from Rydh (1999, p. 23). The other processes are directly taken from NEEDS life cycle results (photovoltaics, wind, gas power plant) and respective ecoinvent unit processes (all others))

the electricity system includes a high share of renewable energies, some CO2 emissions still remain in the life cycle, particularly due to material production processes. The high values of the NiMH and lead acid batteries could be reduced by increasing the cycle lifetime significantly. The results for the lithium-ion battery, pumped hydro and the electrolyser are about equally high with the option of applying pumped hydro in alpine regions showing lower life cycle effects than in non-alpine regions. Furthermore, results for photovoltaic systems, representing a

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situation with low effects and one with high effects, and for a wind offshore plant, based on results from the NEEDS life cycle database (NEEDS 2010), are shown. These concur over a potential over-installation of plants. However, it has to be born in mind that the effects per produced energy unit will clearly increase with a decrease in usage, and thus in the total electricity produced by the plant, which has to be considered in case of over-installation. In total, the external costs estimated for the natural gas combined cycle plant, also represented here, with post-combustion carbon capture and storage (CCS) technology projected to 2050 (NEEDS 2010) are high, but lower than for NiMH batteries and at about the same level as lead-acid batteries per kWh electricity produced or stored and delivered respectively. Climate change effects still dominate the results for the gas power plant, although carbon is captured and stored. Assuming the value of 280 €/tCO2 for the evaluation, particularly the external costs of the gas combined cycle (CC) plant with CCS would increase by a factor of three. The ranking between the storage technologies changes only slightly. In contrast, assuming the value indicating the lower bound of 20 €/tCO2, the total external costs assessed for the gas CC plant with CCS would reduce by about a factor of two. In that case, the ranking remains mainly unchanged. The error bars drawn in the diagram represent the maximum range by assuming the discussed values on marginal climate changes damage costs and on life years lost. However, although these represent major uncertainties in the analysis, further uncertainties exist which are not considered in the error bars. Nonetheless, the results can be used to get an impression of the strengths and weaknesses of the different technologies in terms of environmental impacts, and show in which order of magnitude the resulting external costs are. Beyond the use of storage systems, changes in energy supply systems make it necessary to expand the electricity grids to function on different voltage levels (see Sect. 6.1). Depending on the balancing strategies, the voltage needs can be higher or lower. Such an expansion has to be considered particularly if the chosen strategy is an over-installation of photovoltaic and wind power plants, because it increases the power of remote solar and wind plants and, thus, the required network capacity. This is not necessarily the case for storage options. Accordingly, in addition to the external costs of storage systems, the grid connections are analysed with respect to external costs. Figure 5.7 shows the estimated external costs associated with the construction of transmission and distribution lines. The lines represent average technologies of today’s networks as defined within ecoinvent 2.2 (Ecoinvent 2010). The external costs are calculated as if the technologies are still in use in 2050. The estimated effects for high-voltage grids are dominated by the results for climate change. The reason is the high levels of CO2 emissions in the steel and aluminium production processes. The error bars indicate the maximal variations by applying the values for climate change effects and years of life lost from the sensitivity analysis, as discussed above (Fig. 5.8).

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20 18

NH3, toxics & radionuclides NMVOC

16 14

NOX primary particles SO2

Euro/m

12

CO2

10 8 5.5 6 4

3.2

4.0

2 0 distribution network

transmission medium voltage

transmission high voltage

Fig. 5.8 External costs in 2050 of analysed transmission and distribution lines in € per metre (m) line constructed, calculated for a lifetime of 30 years (Data were taken from ecoinvent 2.2. Data for steel production were adjusted to German conditions, assuming 500 m for the distance between masts)

5.7.2.3 Environmental Impacts of Balancing Technologies Differentiated into Categories Figure 5.9 shows the results for the assessment of impact categories following the assumptions used in the CML 2001 evaluation framework. In addition to relevant storage technologies,7 photovoltaic and wind power plants as well as further gas power plants as projected in NEEDS (2010) are considered: a gas combined cycle (CC) plant with post combustion carbon capture and storage (CCS) technology (500 MW) as considered in the external costs analysis, a gas turbine (50 MW) and the gas combined cycle plant without CCS technology (500 MW). The presentation of individual impacts allows the development of a more differentiated picture of environmental effects. In contrast to the assessed external costs which typically include only small marginal effects, not covering critical environmental damages (see Sect. 2.2.1), the evaluation in impact categories shows potential outcomes which also include critical effects with potentially unacceptable impacts such as eutrophication, acidification, land use, depletion of the ozone layer and the greenhouse effect.

7 The NiMH battery technology has been left out here because it is not as relevant as the options of lead-acid and lithium-ion batteries and would dominate the results.

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0.5 0.4 0.3 0.2 0.1 0

Global warming (GWP100) kg CO2equ.

Eutrophication 600 400 200 0

4,000 3,000 2,000 1,000 0

Fresh water aquatic ecotox.

Marine aquatic ecotoxicity

Photochemical oxidation kg C2H4equ.

Terrestrial ecotoxicity

0.1

0.03 0.02 0.01 gas turbine

gas CC 500MW

wind-offshore

gas CC-CCS 500MW

photovoltaics, high effects

electrolyser (for H2-stor.)

photovoltaics, low effects

gas turbine

gas CC 500MW

wind-offshore

gas CC-CCS 500MW

photovoltaics, high effects

electrolyser (for H2-stor.)

photovoltaics, low effects

pumped hydro alpin

pumped hydro non-alpin

lead-acid battery

lithium-Ion-battery

lead-acid battery

0

0

lithium-lon-battery

0.2

kg 1,4-DB equ.

kg 1,4-DB equ.

14 12 10 8 6 4 2 0

Human toxicity 80 60 40 20 0

t 1,4-DB equ.

g CFC-11 equ.

0.08 0.06 0.04 0.02 0

kg 1,4-DB equ.

Ozone layer depletion (ODP)

pumped hydro alpin

0.08 0.06 0.04 0.02 0

Acidification kg SO2equ.

kg Sb equ. kg PO42-equ.

Abiotic depletion 5 4 3 2 1 0

pumped hydro non-alpin

5.7

Fig. 5.9 Environmental impacts per MWhel by existing storage technologies, photovoltaic and wind power, and three options for using natural gas. The assumption is based on projections for 2050 conditions, which is the scenario “very optimistic” of the NEEDS project and which assumes 80% electricity production from renewable resources (see Sect. 3.1.3)

The pumped hydro plants and the electrolyser show the best performance in all categories. The lithium-ion battery performs worse than these technologies, but at a level similar to the electrolyser and better than other options, except for in the categories eutrophication and fresh water aquatic ecotoxicity. The lead-acid battery shows high effects, particularly in the area of acidification, fresh water aquatic

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ecotoxicity, terrestrial ecotoxicity and photochemical oxidation. The natural gas power plants dominate the categories of abiotic depletion, ozone layer depletion and global warming. Building more wind and photovoltaic power plants in particular would have an effect on marine aquatic and terrestrial ecotoxicity.

5.7.3

Resource Use

5.7.3.1 Types and Amounts of Resources Required Many mineral resources are used for energy storage and transmission and distribution lines. As we have already seen above, in the results relating to the environmental impacts associated with the production of energy storage technologies, energy storage, transmission and distribution lines, these are the main sources of SO2 and CO2 emissions when the electricity mix is dominated by renewable energies. Table 5.17 gives an overview of the amount of minerals used in batteries per kWh electricity produced during the lifetime of the battery. The information in the table allows a prediction of the extent to which various mineral materials would be required in a future energy system using the listed battery technologies at current development status. As lithium-based, lead-acid and vanadium redox-flow batteries Table 5.17 Minerals used for different battery types in percentage of weight considering the whole life cycle following Rydh and Sv€ard (2003, p. 172) and Rydh (1999, p. 23) Substance NiCd NiMH NiMH LiLeadVanadium (AB5) (AB2) based acid redox-flow Aluminium 0.019 0.5–2.0 0.5–1.0 4.6–24 Cadmium 15–20 Cerium 0.43–5.5 Cobalt 0.60 2.5–4.3 1.0–3.0 12–20 Chromium 0.017 0.02–0.08 0–1.6 Copper 5.0–10 0.3 0.8 Iron 29–40 20–25 23–25 4.7–25 Lanthanum 1.4–6.6 Lead 61 Lithium 1.5–5.5 Manganese 0.083 0.81–3.0 10–15 Neodymium 0.96–4.1 Nickel 15–20 25–46 34–39 12–15 Praseodymium 0.32–1.3 Titanium 2.2–3.9 Vanadium 2.2–4.7 15–20 5.6 Zinc 0.060 0.092–1.6 Zirconium 3.9–8.7 Antimony, tin, arsenic 2.1

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represent the most important options for stationary applications (see Sect. 5.2.3), the most important metals for this study are aluminium, antimony, arsenic, cobalt, copper, iron, lead, lithium, manganese, nickel, tin and vanadium. It is important to remember that many of these materials will also be required for electrolysers, gas turbines, fuel cells and other uses. Thus, the list of materials of interest is longer than that mentioned above. In the following, the situation of an extended list of materials will be discussed with respect to the reserves-to-production ratio and supply-side concentrations. These figures are generated based on general data for resource availability and production.

5.7.3.2 Current Availability of Relevant Mineral Resources Table 5.18 focuses on relevant mineral resource data. High prices show there is a scarcity of a mineral. The highest prices currently being paid, especially for platinum group metals, are in the range of millions of US dollars per tonne. Even if only small amounts of these metals are needed, it could lead to high production costs. The largest increases of prices between 2001 and 2006 were observed for cadmium (470%), nickel (460%) and zinc (450%), followed by copper (350%) and cobalt (250%). Also high increases (>100%) were observed for bauxite, chromium, iron, manganese, platinum, and zi