The Future European Energy System : Renewable Energy, Flexibility Options and Technological Progress.
| Main Author: | |
|---|---|
| Other Authors: | , , , , |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing AG,
2021.
|
| Edition: | 1st ed. |
| Subjects: | |
| Online Access: | Click to View |
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.