Technological Learning in the Transition to a Low-Carbon Energy System: Conceptual Issues, Empirical Findings, and Use in Energy Modeling quantifies key trends and drivers of energy technologies deployed in the energy transition. It uses the experience curve tool to show how future cost reductions and cumulative deployment of these technologies may shape the future mix of the electricity, heat and transport sectors. The book explores experience curves in detail, including possible pitfalls, and demonstrates how to quantify the ‘quality’ of experience curves. It discusses how this tool is implemented in models and addresses methodological challenges and solutions.
For each technology, current market trends, past cost reductions and underlying drivers, available experience curves, and future prospects are considered. Electricity, heat and transport sector models are explored in-depth to show how the future deployment of these technologies—and their associated costs—determine whether ambitious decarbonization climate targets can be reached - and at what costs. The book also addresses lessons and recommendations for policymakers, industry and academics, including key technologies requiring further policy support, and what scientific knowledge gaps remain for future research.
1. Part I: Introduction and methods - p. xiv 2. Chapter 1. Introduction - p. 3 3. Chapter 2. The experience curve: concept, history, methods, and issues - p. 9 4. Chapter 3. Implementation of experience curves in energy-system models - p. 33 5. Chapter 4. Application of experience curves and learning to other fields - p. 49 6. Part II: Case studies - p. 61 7. Chapter 5. Photovoltaic solar energy - p. 65 8. Chapter 6. Onshore wind energy - p. 87 9. Chapter 7. Offshore wind energy - p. 103 10. Chapter 8. Grid-scale energy storage - p. 119 11. Chapter 9. Electric vehicles - p. 145 12. Chapter 10. Power to gas (H2): alkaline electrolysis - p. 165 13. Chapter 11. Heating and cooling in the built environment - p. 189 14. Chapter 12. Concentrating solar power - p. 221 15. Chapter 13. Light-emitting diode lighting products - p. 233 16. Part III: Application of experience curves in modeling - p. 254 17. Chapter 14. Experience curves in energy models—lessons learned from the REFLEX project - p. 259 18. Chapter 15. Global electric car market deployment considering endogenous battery price development - p. 281 19. Part IV: Final words - p. 303 20. Chapter 16. Synthesis, conclusions, and recommendations - p. 309 21. Index - p. 321
Technological Learning in the Transition to a Low-Carbon Energy System: Conceptual Issues, Empirical Findings, and Use in Energy Modeling quantifies key trends and drivers of energy technologies deployed in the energy transition. It uses the experience curve tool to show how future cost reductions and cumulative deployment of these technologies may shape the future mix of the electricity, heat and transport sectors. The book explores experience curves in detail, including possible pitfalls, and demonstrates how to quantify the ‘quality’ of experience curves. It discusses how this tool is implemented in models and addresses methodological challenges and solutions.
For each technology, current market trends, past cost reductions and underlying drivers, available experience curves, and future prospects are considered. Electricity, heat and transport sector models are explored in-depth to show how the future deployment of these technologies—and their associated costs—determine whether ambitious decarbonization climate targets can be reached - and at what costs. The book also addresses lessons and recommendations for policymakers, industry and academics, including key technologies requiring further policy support, and what scientific knowledge gaps remain for future research.
1. Part I: Introduction and methods - p. xiv 2. Chapter 1. Introduction - p. 3 3. Chapter 2. The experience curve: concept, history, methods, and issues - p. 9 4. Chapter 3. Implementation of experience curves in energy-system models - p. 33 5. Chapter 4. Application of experience curves and learning to other fields - p. 49 6. Part II: Case studies - p. 61 7. Chapter 5. Photovoltaic solar energy - p. 65 8. Chapter 6. Onshore wind energy - p. 87 9. Chapter 7. Offshore wind energy - p. 103 10. Chapter 8. Grid-scale energy storage - p. 119 11. Chapter 9. Electric vehicles - p. 145 12. Chapter 10. Power to gas (H2): alkaline electrolysis - p. 165 13. Chapter 11. Heating and cooling in the built environment - p. 189 14. Chapter 12. Concentrating solar power - p. 221 15. Chapter 13. Light-emitting diode lighting products - p. 233 16. Part III: Application of experience curves in modeling - p. 254 17. Chapter 14. Experience curves in energy models—lessons learned from the REFLEX project - p. 259 18. Chapter 15. Global electric car market deployment considering endogenous battery price development - p. 281 19. Part IV: Final words - p. 303 20. Chapter 16. Synthesis, conclusions, and recommendations - p. 309 21. Index - p. 321
