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Summary of IEA Report on Experience Curves for Energy Technology Policy

1 Introduction to IEA and Experience Curves

The IEA is an autonomous body established within the OECD to implement an international energy program. It comprises 29 member countries and focuses on maintaining oil supply systems, promoting rational energy policies, and advancing energy technology through R&D and deployment support.

Experience curves represent long-term strategic concepts showing how cumulative production leads to lower prices through learning and efficiency gains. They demonstrate that investment in deployment could drive prices down so as to provide new competitive energy systems for CO₂ stabilization. Key findings:

• Prices follow a power function relationship with cumulative production
• Most progress ratios observed are around 82% progress ratio or 18% learning rate
• Experience curves provide quantitative basis for policy analysis

2 Methodology and Theory

2.1 Learning Model

• Basic input-output model where performance improves as output increases
• Learning effect captured by the experience curve equation: Price = P₀ * X⁻ᴱ
• Progress ratio (PR=2⁻ᴱ) measures percentage price reduction after cumulative production doubles

2.2 Experience Curve Construction

• Base for understanding future markets
• Demonstrates historical development
• Provides benchmarks for future projections
• Addresses policy questions on support levels

2.3 Technology Learning

• Experience represents cumulative transformation effort
• Progress ratio indicates learning rate
• Bottlenecks or technological change may alter the curve

3 Case Studies and Policy Applications

3.1 Solar Heating in Germany

• Federal RD&D program from 1975-1987
• Average progress ratio of 70%
• Break-even reached with cumulative production of ~600 GW
• Learning investments ($10-25 billion) mostly funded by public initially

3.2 Wind Power Deployment

• German 100/250 MW program provided catalyst
• Experience curve with ~92% progress ratio
• Subsidies reduced as prices fell, maintaining constant price-margin ratio

3.3 Japanese PV Systems Program (PV-Roof)

• Niche market creation for residential PV systems
• Target prices of 3-5 US$/Wp by 2000-2007
• Learning investments reached ~$1.5 billion for self-sustaining niche market
• Requires multinational collaboration to meet growing niche demands

4 Dynamic Learning and Technology Competition

4.1 Experience Curve Dynamics

• Steep learning rates for supply technologies
• Explicit need for long-term stable policies
• Questions of allocation between fixed learning investments

4.2 Modeling Results

• MARKAL/Genie models indicate self-sustaining low-carbon systems are possible
• Global learning is essential but market transformation must occur locally
• Technology portfolios need balancing between risk diversification and efficiency

4.3 Competition for Investments

• Scarce learning opportunities require prioritization decisions
• Learning investments are recovered over product lifetime
• Top-down analysis complements bottom-up approaches

5 Policy Implications and Conclusions

5.1 Strategic Policy Decisions

• Portfolio of climate-friendly supply technologies needed
• Long-term stable policies required to overcome technical locks
• Concerted national action needed to meet future challenges

5.2 Policy Monitoring

• Real-time monitoring through experience curves
• Economic viability assessment
• Strategic planning for deployment

5.3 Institutional Balance

• Global coherence needed for standardized learning curves
• Local autonomy necessary for market adaptation
• International collaboration mechanisms needed to manage CO₂ stabilization

5.4 Recommendations

1. Apply experience curves to analyze cost-benefits of environment-friendly technology programs
2. Explicitly consider experience effect in CO₂ reduction scenario exploration
3. Establish international collaboration on experience curves for energy technology policy
4. Study technology spill-over effects and government action needs

The report emphasizes that proactive, globally-oriented strategies based on portfolios of generic technologies are necessary to provide cost-efficient CO₂ mitigation technologies by the middle of the new century, requiring appropriate international co-operation on technology deployment policies.