The Future European Energy System : : Renewable Energy, Flexibility Options and Technological Progress.

• Author: Möst, Dominik.
• TeilnehmendeR: Schreiber, Steffi.; Herbst, Andrea.; Jakob, Martin.; Martino, Angelo.; Poganietz, Witold-Roger.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2021.; ©2021.
• Year of Publication: 2021
• Language: English
• Physical Description: 1 online resource (321 pages)

This open access book analyzes the transition toward a low-carbon energy system in Europe under the aspects of flexibility and technological progress. By covering the main energy sectors – including the industry, residential, tertiary and transport sector as well as the heating and electricity secto...

Table of Contents

• Intro
• Foreword
• Acknowledgments
• Contents
• Editors and Contributors
• About the Editors
• Contributors
• List of Figures
• List of Tables
• Part IIntroduction, Scenario Description and Model Coupling Approach
• 1 Introduction
• Reference
• 2 Scenario Storyline in Context of Decarbonization Pathways for a Future European Energy System
• 2.1 Introduction
• 2.2 Scenario Definition and General Drivers
• 2.3 Socio-Technical Scenario Framework
• 2.4 Moderate Renewable Energy Source Scenario (Mod-RES)
• 2.5 Centralized versus Decentralized High Renewable Scenario (High-RES)
• 2.5.1 Centralized High-RES Scenario
• 2.5.2 Decentralized High-RES Scenario
• 2.6 Conclusions
• References
• 3 Model Coupling Approach for the Analysis of the Future European Energy System
• 3.1 Introduction
• 3.2 Description of Applied Models
• 3.2.1 ELTRAMOD
• 3.2.2 TIMES-Heat-EU
• 3.2.3 PowerACE
• 3.2.4 FORECAST
• 3.2.5 eLOAD
• 3.2.6 ASTRA
• 3.2.7 TE3
• 3.2.8 eLCA and sLCA
• 3.2.9 πESA
• 3.3 REFLEX Energy Models System
• References
• Part IITechnological Progress
• 4 Deriving Experience Curves and Implementing Technological Learning in Energy System Models
• 4.1 Introduction
• 4.1.1 History and Concept
• 4.1.2 Key Applications of Experience Curves
• 4.1.3 Key Issues and Drawbacks of Experience Curves
• 4.2 Data Collection and Derivation of Experience Curves
• 4.2.1 Functional Unit and System Boundaries
• 4.2.2 Correction for Currency and Inflation
• 4.2.3 Deriving Experience Curve Parameters
• 4.3 Experience Curves in Energy System Models
• 4.3.1 Model Implementation of Experience Curves
• 4.3.2 Issues with Implementation of Experience Curves in Energy Models
• 4.3.3 Description of Energy Models with Implemented Experience Curves
• 4.4 State-of-the-Art Experience Curves and Modeling Results.
• 4.4.1 Overview of State-of-the-Art Experience Curves
• 4.4.2 Deployments and Cost Developments of Relevant Technologies
• 4.5 Lessons Learned
• 4.5.1 Methodological Issues
• 4.5.2 Model Implementation Issues
• 4.6 Conclusions
• References
• 5 Electric Vehicle Market Diffusion in Main Non-European Markets
• 5.1 Introduction
• 5.1.1 Motivation
• 5.1.2 Related Research and Research Question
• 5.2 Considering Experience Curves in Market Diffusion Modeling and Scenario Definition
• 5.2.1 The TE3 Model and Implementation of Experience Curves
• 5.2.2 Framework of the Two Analyzed Scenarios for the Main Non-European Car Markets
• 5.3 Results of Key Non-European Countries
• 5.3.1 Effects on Cumulative Battery Capacity and Battery Costs
• 5.3.2 Development of the Car Stock for the Four Main Markets in the Mod-RES and High-RES Scenario
• 5.3.3 Critical Review and Limitations
• 5.4 Summary and Conclusions
• References
• Part IIIDemand Side Flexibility and the Role of Disruptive Technologies
• 6 Future Energy Demand Developments and Demand Side Flexibility in a Decarbonized Centralized Energy System
• 6.1 Introduction
• 6.2 Scenario Assumptions and Model Coupling
• 6.3 Future Energy Demand and CO2 Emissions
• 6.3.1 Decarbonizing the Transport Sector
• 6.3.2 Decarbonizing the Residential and Tertiary Sector
• 6.3.3 Decarbonizing the Industry Sector
• 6.4 The Future Need for Demand Side Flexibility
• 6.5 Conclusions
• References
• 7 Disruptive Demand Side Technologies: Market Shares and Impact on Flexibility in a Decentralized World
• 7.1 Introduction
• 7.1.1 Strategies for Decarbonizing Transport
• 7.1.2 Technologies for Decarbonizing Industry
• 7.1.3 Focus of this Study: Disruptive Technologies with Demand Side Flexibility
• 7.2 Disruptive Technologies with Flexibility Potential.
• 7.2.1 Photovoltaic Systems and Stationary Batteries
• 7.2.2 Battery Electric Vehicles
• 7.2.3 Hydrogen Electrolysis
• 7.3 Scenario Assumptions and Methodology
• 7.3.1 Scenario Assumptions for High-RES Decentralized
• 7.3.2 Model Coupling Approach
• 7.3.3 Methods Used for Technology Diffusion
• 7.4 Results: Diffusion of Technologies and Energy Demand
• 7.4.1 Installed Battery Capacity
• 7.4.2 Vehicle Fleet Technology Composition and Resulting Energy Demand
• 7.4.3 Radical Process Improvements in Industry and Their Implications for Future Electricity Demand
• 7.5 Impacts of Disruptive Technologies on Demand Side Flexibility
• 7.6 Discussion and Conclusions
• References
• 8 What is the Flexibility Potential in the Tertiary Sector?
• 8.1 Introduction
• 8.1.1 Overview of Demand Side Flexibility Markets
• 8.1.2 Overview of Tertiary Sector and Potential Applications, Regulatory Environment
• 8.2 Data Collection Methodology
• 8.2.1 Research Questions
• 8.2.2 Empirical Survey Introduction
• 8.2.3 Issues Encountered Regarding Empirical Data
• 8.3 Survey Results and Derived Flexibility Potentials
• 8.3.1 Participation Interest in DSM
• 8.3.2 Available Technologies
• 8.3.3 Derived Flexibility Potentials (S-Curve)
• 8.3.4 Lessons Learned and Issues Identified for Modelers
• 8.4 Conclusions and Recommendations for Further Research
• References
• 9 A Techno-Economic Comparison of Demand Side Management with Other Flexibility Options
• 9.1 Introduction
• 9.2 Techno-Economic Characteristics of DSM in Comparison with Other Flexibility Options
• 9.2.1 Technical Characteristics of DSM
• 9.2.2 Activation and Initialization Costs of DSM
• 9.3 Impact of DSM on Other Flexibility Options
• 9.3.1 Framework of the Analysis
• 9.3.2 Impact of DSM on the Operation of Conventional Power Plants and Pump Storage Plants.
• 9.3.3 Impact of DSM on Imports and Exports
• 9.4 Conclusions
• References
• Part IVFlexibility Options in the Electricity and Heating Sector
• 10 Optimal Energy Portfolios in the Electricity Sector: Trade-Offs and Interplay Between Different Flexibility Options
• 10.1 Introduction
• 10.2 Data Input and Model Coupling
• 10.3 Optimal Investments in Flexibility Options
• 10.3.1 Sector Coupling Technologies
• 10.3.2 Power Plant Mix
• 10.3.3 Storages
• 10.4 Sensitivity Analyses
• 10.4.1 Impact of Limited DSM Potential and Reduced Battery Investment Costs on the Storage Value in the Electricity Market
• 10.4.2 Impact of Higher Shares of Renewable Energy Sources
• 10.5 Levelized Costs of Electricity and CO2 Abatement Costs
• 10.6 Discussion and Conclusion
• References
• 11 Impact of Electricity Market Designs on Investments in Flexibility Options
• 11.1 The European Debate on Electricity Market Design
• 11.2 Research Design
• 11.3 Development of the Conventional Generation Capacities and Wholesale Electricity Prices
• 11.3.1 Mod-RES Scenario
• 11.3.2 High-RES Decentralized Scenario
• 11.3.3 High-RES Centralized Scenario
• 11.4 Impact on Generation Adequacy
• 11.5 Summary and Conclusions
• References
• 12 Optimal Energy Portfolios in the Heating Sector and Flexibility Potentials of Combined-Heat-Power Plants and District Heating Systems
• 12.1 Introduction
• 12.2 TIMES-Heat-EU Model
• 12.3 Developments in the District Heating Sector
• 12.3.1 Scenario Results
• 12.3.2 CO2 Emissions in the Heating Sector
• 12.3.3 Sensitivity Analysis
• 12.4 Conclusion
• References
• Part VAnalysis of the Environmental and Socio-Impacts beyond the Greenhouse Gas Emission Reduction Targets
• 13 Unintended Environmental Impacts at Local and Global Scale-Trade-Offs of a Low-Carbon Electricity System
• 13.1 Introduction.
• 13.2 Developing the Model Coupling Approach to Identify Environmental Trade-Offs
• 13.2.1 Describing Relevant Input Parameters for the LCA Model in Context of the REFLEX Scenarios
• 13.2.2 Coupling the Results of ELTRAMOD and the LCA Model to Determine Policy Implications
• 13.3 Unintended Environmental Consequences of the European Low-Carbon Electricity System
• 13.3.1 Environmental Impacts at Local Scale and the Challenges for European Member States
• 13.3.2 Resource Depletion in REFLEX Mitigation Scenarios as a Backdrop of Global Trade Uncertainty
• 13.4 Conclusions and Policy Implications
• References
• 14 Assessing Social Impacts in Current and Future Electricity Production in the European Union
• 14.1 Introduction
• 14.2 Method
• 14.2.1 Background to the SOCA Add-on for Social Life Cycle Assessment
• 14.2.2 Establishing the Life Cycle Model for Social Assessment
• 14.2.3 Social Impact Categories
• 14.2.4 Calculation Method
• 14.2.5 Contribution Analysis
• 14.3 Results
• 14.4 Concluding Discussion and Policy Implications
• References
• 15 Spatially Disaggregated Impact Pathway Analysis of Direct Particulate Matter Emissions
• 15.1 Introduction
• 15.2 Description of the Method
• 15.2.1 Emission Scenarios
• 15.2.2 Air Quality Modeling
• 15.2.3 Health Impacts and External Costs
• 15.3 Results
• 15.3.1 Summary and Conclusions
• References
• Part VIConcluding Remarks
• 16 Summary, Conclusion and Recommendations
• 16.1 Summary
• 16.1.1 Electricity Sector
• 16.1.2 Demand Side Sectors
• 16.1.3 Environmental Impacts
• 16.2 Conclusions and Recommendations
• 16.2.1 Electricity Sector
• 16.2.2 Industry Sector
• 16.2.3 Transport Sector
• 16.2.4 Heating Sector
• 16.2.5 Environmental, Social Life Cycle and Health Impact Assessment
• 16.3 Further Aspects and Outlook
• References.