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Stochastic Wind Power Generation Planning in Liberalised Electricity Markets within a Heterogeneous Landscape

Author

Listed:
  • Lennard Sund

    (Faculty of Management, Economics and Social Sciences, University of Cologne, 50923 Cologne, Germany)

  • Saber Talari

    (Faculty of Management, Economics and Social Sciences, University of Cologne, 50923 Cologne, Germany)

  • Wolfgang Ketter

    (Faculty of Management, Economics and Social Sciences, University of Cologne, 50923 Cologne, Germany
    Rotterdam School of Management, Erasmus University Rotterdam, 3062 PA Rotterdam, The Netherlands)

Abstract

Spatially separated locations may differ greatly with respect to their electricity demand, available space, and local weather conditions. Thus, the regions that are best suited to operating wind turbines are often not those where electricity is demanded the most. Optimally, renewable generation facilities are constructed where the maximum generation can be expected. With transmission lines limited in capacity though, it might be economically rational to install renewable power sources in geographically less favourable locations. In this paper, a stochastic bilevel optimisation is developed as a mixed-integer linear programme to find the socially optimal investment decisions for generation expansion in a multi-node system with transmission constraints under an emissions reduction policy. The geographic heterogeneity is captured by using differently skewed distributions as a basis for scenario generation for wind speeds as well as different opportunities to install generation facilities at each node. The results reinforce that binding transmission constraints can greatly decrease total economic and emissions efficiency, implying additional incentives to enhance transmission capacity between the optimal supplier locations and large demand centres.

Suggested Citation

  • Lennard Sund & Saber Talari & Wolfgang Ketter, 2022. "Stochastic Wind Power Generation Planning in Liberalised Electricity Markets within a Heterogeneous Landscape," Energies, MDPI, vol. 15(21), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8109-:d:959063
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    References listed on IDEAS

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