Technological Learning in the Transition to a Low-Carbon Energy System: Conceptual Issues, Empirical Findings, and Use, in Energy Modeling

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.

Provides a comprehensive overview of trends and drivers for major energy technologies expected to play a role in the energy transitionDelivers data on cost trends, helping readers gain insights on how competitive energy technologies may become, and whyReviews the use of learning curves in environmental impacts for lifecycle assessments and energy modelingFeatures social learning for cost modeling and technology diffusion, including where consumer preferences play a major role

Part I 1. Introduction 2. The Experience Curve: Concept, History, Methods and Issues 3. Implementation of Experience Curves in Energy energy-system models 4. Application of experience curves and learning to other fields Part II Case Studies 5. Photovoltaic solar energy 6. Onshore wind energy 7. Offshore wind energy 8. Grid-scale energy storage 9. Electric Vehicles 10. Power to gas (H2): alkaline electrolysis 11. Heating and cooling in the built environment 12. Concentrating solar power 13. Light-emitting diode lighting products Part III Application of Experience Curves in Modeling 14. Experience Curves in Energy Models by Lessons Learned from the REFLEX project 15. Global electric car market deployment considering endogenous battery price development Part IV Final words 16. Synthesis, conclusions, and recommendations