Journal of Modern Power Systems and Clean Energy (Jan 2022)

Statistical Measure for Risk-seeking Stochastic Wind Power Offering Strategies in Electricity Markets

  • Dongliang Xiao,
  • Haoyong Chen,
  • Chun Wei,
  • Xiaoqing Bai

DOI
https://doi.org/10.35833/MPCE.2021.000218
Journal volume & issue
Vol. 10, no. 5
pp. 1437 – 1442

Abstract

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This study proposes a statistical measure and a stochastic optimization model for generating risk-seeking wind power offering strategies in electricity markets. Inspired by the value at risk (VaR) to quantify risks in the worst-case scenarios of a profit distribution, a statistical measure is proposed to quantify potential high profits in the best-case scenarios of a profit distribution, which is referred to as value at best (VaB) in the best-case scenarios. Then, a stochastic optimization model based on VaB is developed for a risk-seeking wind power producer, which is formulated as a mixed-integer linear programming problem. By adjusting the parameters in the proposed model, the wind power producer can flexibly manage the potential high profits in the best-case scenarios from the probabilistic perspective. Finally, the proposed statistical measure and riskseeking stochastic optimization model are verified through case studies.

Keywords