DOI:10.35833/MPCE.2021.000218 |
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Statistical Measure for Risk-seeking Stochastic Wind Power Offering Strategies in Electricity Markets |
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Net amount: 368 |
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Author:
Xiao Dongliang1, Chen Haoyong1, Wei Chun2, Bai Xiaoqing3
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Author Affiliation:
1.School of Electric Power, South China University of Technology, Guangzhou 510641, China 2.College of Information Engineering, Zhejiang University of Technology, Hangzhou, China 3.School of Electrical Engineering, Guangxi University, Nanning, China
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Foundation: |
This work was supported by the National Natural Science Foundation of Guangdong Province (No. 2019A1515010689). |
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Abstract: |
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 risk-seeking stochastic optimization model are verified through case studies. |
Keywords: |
Electricity market ; risk-seeking ; statistical measure ; stochastic optimization ; wind power |
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Received:April 04, 2021
Online Time:2022/09/24 |
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