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Learning curves and changing product attributes: the case of wind turbines

Author

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  • Coulomb, L.
  • Neuhoff, K.

Abstract

The heuristic concept of learning curves describes cost reductions as a function of cumulative production. A study of the Liberty shipbuilders suggested that product quality and production scale are other relevant factors that affect costs. Significant changes of attributes of a technology must be corrected when assessing the impact of learning-by-doing. We use an engineering-based model to capture the cost changes of wind turbines that can be attributed to changes in turbine size. We estimate the learning curve and turbine size parameters using more than 1500 price points from 1991 to 2003. The fit between model and empirical data confirms the concept.

Suggested Citation

  • Coulomb, L. & Neuhoff, K., 2006. "Learning curves and changing product attributes: the case of wind turbines," Cambridge Working Papers in Economics 0618, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:0618 Note: IO
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    File URL: http://www.electricitypolicy.org.uk/pubs/wp/eprg0601.pdf
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    References listed on IDEAS

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    1. Goldemberg, Jose, 1996. "The evolution of ethanol costs in Brazil," Energy Policy, Elsevier, vol. 24(12), pages 1127-1128, December.
    2. Peter Thompson, 2001. "How Much Did the Liberty Shipbuilders Learn? New Evidence for an Old Case Study," Journal of Political Economy, University of Chicago Press, vol. 109(1), pages 103-137, February.
    3. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
    4. Isoard, Stephane & Soria, Antonio, 2001. "Technical change dynamics: evidence from the emerging renewable energy technologies," Energy Economics, Elsevier, vol. 23(6), pages 619-636, November.
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    Citations

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    Cited by:

    1. Peter Hartley, Kenneth B. Medlock III, Ted Temzelides, Xinya Zhang, 2016. "Energy Sector Innovation and Growth: An Optimal Energy Crisis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    2. Wilson, Charlie, 2012. "Up-scaling, formative phases, and learning in the historical diffusion of energy technologies," Energy Policy, Elsevier, vol. 50(C), pages 81-94.
    3. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
    4. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
    5. Yu, Yang & Li, Hong & Che, Yuyuan & Zheng, Qiongjie, 2017. "The price evolution of wind turbines in China: A study based on the modified multi-factor learning curve," Renewable Energy, Elsevier, vol. 103(C), pages 522-536.
    6. Marc Baudry & Clément Bonnet, 2016. "Demand pull isntruments and the development of wind power in Europe: A counter-factual analysis," Working Papers 1607, Chaire Economie du climat.
    7. Neuhoff, Karsten & Ehrenmann, Andreas & Butler, Lucy & Cust, Jim & Hoexter, Harriet & Keats, Kim & Kreczko, Adam & Sinden, Graham, 2008. "Space and time: Wind in an investment planning model," Energy Economics, Elsevier, vol. 30(4), pages 1990-2008, July.
    8. repec:eee:respol:v:46:y:2017:i:10:p:1873-1886 is not listed on IDEAS
    9. Qiu, Yueming & Anadon, Laura D., 2012. "The price of wind power in China during its expansion: Technology adoption, learning-by-doing, economies of scale, and manufacturing localization," Energy Economics, Elsevier, vol. 34(3), pages 772-785.
    10. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, Open Access Journal, vol. 9(11), pages 1-25, November.
    11. Dosi, Giovanni & Grazzi, Marco & Mathew, Nanditha, 2017. "The cost-quantity relations and the diverse patterns of “learning by doing”: Evidence from India," Research Policy, Elsevier, pages 1873-1886.
    12. Berry, David, 2009. "Innovation and the price of wind energy in the US," Energy Policy, Elsevier, vol. 37(11), pages 4493-4499, November.
    13. Ambec, Stefan & Crampes, Claude, 2012. "Electricity provision with intermittent sources of energy," Resource and Energy Economics, Elsevier, vol. 34(3), pages 319-336.
    14. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    15. Hong, Sungjun & Chung, Yanghon & Woo, Chungwon, 2015. "Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea," Energy, Elsevier, vol. 79(C), pages 80-89.

    More about this item

    Keywords

    Learning curve; Turbine scale; Wind turbines;

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • N70 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - General, International, or Comparative
    • L64 - Industrial Organization - - Industry Studies: Manufacturing - - - Other Machinery; Business Equipment; Armaments
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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