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Exploring the mean-variance portfolio optimization approach for planning wind repowering actions in Spain

Author

Listed:
  • Santos-Alamillos, F.J.
  • Thomaidis, N.S.
  • Usaola-García, J.
  • Ruiz-Arias, J.A.
  • Pozo-Vázquez, D.

Abstract

The repowering of already installed wind farms is considered one of the most promising and cost-effective short-term strategies to scale-up wind capacity. In this study, we apply Markowitz's mean-variance (MV) portfolio optimization theory to explore alternative repowering actions in Spain. The efficient portfolios – a direct outcome of the MV optimization – offer optimal repowering alternatives to current wind farm generation mixes. They deliver the highest possible average power output (yield) for a given level of supply risk. Different repowering scenarios are considered in this paper that range from a full restructuring of the existing wind generation mix to restricting by certain amounts the percentage of down-/uprating of each reference region. Results show that, depending on the configuration of the MV portfolio optimization problem, hourly fluctuations in the aggregate power supply can be reduced as much as 12–31%, while retaining the current level of energy productivity. In addition, for the level of energy supply risk experienced with the existing portfolio of Spanish wind farms; we can derive more efficient mixes that boost-up productivity by 16–55%. This work aims at providing valuable insight for energy policy-making in the direction of optimally repowering future renewable generation.

Suggested Citation

  • Santos-Alamillos, F.J. & Thomaidis, N.S. & Usaola-García, J. & Ruiz-Arias, J.A. & Pozo-Vázquez, D., 2017. "Exploring the mean-variance portfolio optimization approach for planning wind repowering actions in Spain," Renewable Energy, Elsevier, vol. 106(C), pages 335-342.
    • Handle: RePEc:eee:renene:v:106:y:2017:i:c:p:335-342
    DOI: 10.1016/j.renene.2017.01.041
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    References listed on IDEAS

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