Experience Curves for Energy Technology Policy [electronic resource] /
International Energy Agency.
Organisation for Economic Co-operation and DevelopmentContent Provider
International Energy AgencyContent Provider
Organisation for Economic Co operation and DevelopmentContent Provider
Paris : OECD Publishing,
2000.
The fact that market experience improves performance and reduces prices is well known and widely exploited in technology-intensive industries, but sparsely used in analysis for energy technology policy. Knowledge of the “experience effect” can help in the design of efficient programmes for deploying of environment-friendly technologies. The effect must be taken into account when estimating the future costs of achieving targets, including targets for carbon dioxide reduction. This book discusses issues raised by the “experience effect”, such as price-cost cycles, competition for learning opportunities in the market, risk of “technology lockout” and the effects of research, development and deployment policies on technology learning. Case studies illustrate how experience curves can be used to set policy targets and to design policy measures that will encourage both investment in and use of environment-friendly energy technologies. Low-cost paths to stabilising CO2 emissions are explored.
Description based upon print version of record.
Foreword; TABLE OF CONTENTS; List of Figures and Tables Figures; Tables; Chapter 1: Riding on the Experience Curve; Price for an Emerging Technology; Figure 1.1 Experience Curve for PV Modules, 1976-1992; Figure 1.2 Danish Wind Turbines, 1982-1997; Figure 1.3 Distribution of Progress Ratios; Assessing Future Prospects; Figure 1.4 Making Photovoltaics Break-Even; Competition for Learning Opportunities; Figure 1.5 Electric Technologies in EU, 1980-1995; Figure 1.6 District Heating in Sweden, 1980-1995; The Purpose of this Book; Chapter 2: Learning Requires Action
An Input-Output Model of LearningFigure 2.1 Basic Model for a Learning System; Influencing the Learning System: Public R&D and DeploymentPolicies; Figure 2.2 Influences on the Learning System from PublicPolicy; Figure 2.3 A Roadmap for Policies on DecarbonisationEnergy Technologies; Inside the Learning System I: Technology Structural Change; Figure 2.4 Technology Structural Change; Outside the Learning System: Market Structural Change; Figure 2.5 Price-cost Relations for a New Product; Figure 2.6 Natural Gas Combined Cycle, 1981-1997; Figure 2.7 Market Changes for PV Modules, 1976-1996
Figure 2.8 Brazilian Ethanol 1978-1995Inside the Learning System II: Compound Systems; Figure 2.9 US Learning System for Production of Electricityfrom Wind; Figure 2.10 Electricity from Wind Energy in USA, 1985-1994; Chapter 3: Making Emerging Technologies Commercial; Solar Heating - Monitoring and Terminating an RD&DProgramme; Figure 3.1 Solar Heated Swimming Pools: Germany,1975-1997; Figure 3.2 Solar Heated Swimming Pools, 1975-1993:Experience Curve and RD&D Support; Table 3.1 Learning Investments and Federal RD&D Supportfor Solar Heated Swimming Pools
Wind Power - Deployment Support to Increase LearningInvestmentsFigure 3.3 Electricity from Wind Energy in EU, 1980-1995; Figure 3.4 Wind Turbines in Germany, 1990-1998; Figure 3.5 Average Capacity of Wind Turbines Units InstalledEach Year; Figure 3.6 Changing Markets for Wind Turbines in Germany; Figure 3.7 Learning Investments and GovernmentExpenditures; Figure 3.8 Investments in Wind Turbines in Germany; Photovoltaics - Creating and Supporting New Niche Markets; Figure 3.9 Docking PV Technology to Niche Marketsin Japan; Table 3.2 Niche Markets for Photovoltaics in Japan
Figure 3.10 Japan's PV-Roof Programme: Use of NicheMarketsFigure 3.11 Investments and Subsidies in PV-Roof Programme; Figure 3.12 Japan's PV-Roof Programme and World PVMarkets; Figure 3.13 Learning Investments in Residential PV Systems; Chapter 4: The Dynamics of Learning and TechnologyCompetition; Effect of Learning on Estimates of CO 2 Mitigation Cost; Figure 4.1 Carbon Intensity of World Economy, 1971-2020; Figure 4.2 Carbon Intensity Paths, 1971-2060; Figure 4.3 Additional Annual Cost for Photovoltaics; Figure 4.4 Additional Annual Cost for TechnologyPortfolio
Figure 4.5 Present value of Technology Portfolio
Includes bibliographical references.
The fact that market experience improves performance and reduces prices is well known and widely exploited in technology-intensive industries, but sparsely used in analysis for energy technology policy. Knowledge of the “experience effect” can help in the design of efficient programmes for deploying of environment-friendly technologies. The effect must be taken into account when estimating the future costs of achieving targets, including targets for carbon dioxide reduction. This book discusses issues raised by the “experience effect”, such as price-cost cycles, competition for learning opportunities in the market, risk of “technology lockout” and the effects of research, development and deployment policies on technology learning. Case studies illustrate how experience curves can be used to set policy targets and to design policy measures that will encourage both investment in and use of environment-friendly energy technologies. Low-cost paths to stabilising CO2 emissions are explored.
Experiential learning.
Learning models (Stochastic processes)
Energy policy