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Learning Rates in Wind Energy: Cross-country Analysis and Policy Applications for Russia

Author

Listed:
  • Svetlana Ratner

    (Institute of Control Science, Russia,)

  • ?vgenii Khrustalev

    (Central Economics and Mathematics Institute, Russian Academy of Sciences, Russia.)

Abstract

This article performs a meta-analysis of data on learning rates in wind energy, obtained from building single- and dual-factor learning curve models detailed by countries and technology development periods. It reveals a significant difference in learning rates mainly due to design and efficiency of government support programs. Multiple case studies were performed in order to interpret these results. This study proves that the maximal learning rate in wind energy can be achieved by financial support of R&D on the early stage of technological development and by attracting large manufacturers of wind turbines and other electric generation equipment on later stages. Given the fact that wind equipment manufacturing technologies are currently well developed and the global market of wind turbines is highly competitive, the tactic of obtaining technologies in exchange for access to the domestic market may prove successful even with a small domestic market capacity.

Suggested Citation

  • Svetlana Ratner & ?vgenii Khrustalev, 2018. "Learning Rates in Wind Energy: Cross-country Analysis and Policy Applications for Russia," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 258-266.
    • Handle: RePEc:eco:journ2:2018-03-30
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    References listed on IDEAS

    as
    1. Bean, Patrick & Blazquez, Jorge & Nezamuddin, Nora, 2017. "Assessing the cost of renewable energy policy options – A Spanish wind case study," Renewable Energy, Elsevier, vol. 103(C), pages 180-186.
    2. Blind, Knut & Petersen, Sören S. & Riillo, Cesare A.F., 2017. "The impact of standards and regulation on innovation in uncertain markets," Research Policy, Elsevier, vol. 46(1), pages 249-264.
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    Cited by:

    1. Nemet, Gregory F. & Lu, Jiaqi & Rai, Varun & Rao, Rohan, 2020. "Knowledge spillovers between PV installers can reduce the cost of installing solar PV," Energy Policy, Elsevier, vol. 144(C).
    2. Rabbani, Rabab & Zeeshan, Muhammad, 2022. "Impact of policy changes on financial viability of wind power plants in Pakistan," Renewable Energy, Elsevier, vol. 193(C), pages 789-806.

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    More about this item

    Keywords

    wind energy; learning curves; power engineering; economic analysis;
    All these keywords.

    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
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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