Global experience curves for wind farms |
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| Affiliation: | 1. Energy Institute, The University of Texas at Austin, 2304 Whitis Ave, C2400, Austin, TX 78712, USA;2. Center for International Energy and Environmental Policy, Jackson School of Geosciences, The University of Texas at Austin, 2275 Speedway, C9000, Austin, TX 78712, USA;1. School of Management, Hefei University of Technology, Hefei 230009, China;2. Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing 100081, China;3. National Natural Science Foundation of China (NSFC), Beijing 100085, China;4. School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China;1. School of Business Administration, China University of Petroleum, Beijing, China;2. Global Energy Systems, Department of Earth Sciences, Uppsala University, Sweden;1. School of Environment and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China;2. School of International Trade and Economics, University of International Business and Economics, Beijing 100029, China;3. School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China;1. Department of Engineering, University of Perugia, Perugia, Italy;2. DMII, Università degli Studi Guglielmo Marconi, Roma 00193, Italy;3. Sorgenia Green srl, Via Viviani 12, Milano 20124, Italy |
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| Abstract: | In order to forecast the technological development and cost of wind turbines and the production costs of wind electricity, frequent use is made of the so-called experience curve concept. Experience curves of wind turbines are generally based on data describing the development of national markets, which cause a number of problems when applied for global assessments. To analyze global wind energy price development more adequately, we compose a global experience curve. First, underlying factors for past and potential future price reductions of wind turbines are analyzed. Also possible implications and pitfalls when applying the experience curve methodology are assessed. Second, we present and discuss a new approach of establishing a global experience curve and thus a global progress ratio for the investment cost of wind farms. Results show that global progress ratios for wind farms may lie between 77% and 85% (with an average of 81%), which is significantly more optimistic than progress ratios applied in most current scenario studies and integrated assessment models. While the findings are based on a limited amount of data, they may indicate faster price reduction opportunities than so far assumed. With this global experience curve we aim to improve the reliability of describing the speed with which global costs of wind power may decline. |
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