Twostage symmetrical fuzzy modeling and optimization for the unit commitment in wind power systems
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    Abstract:

    In order to solve the problem of uncertainty caused by the inherent prediction error in the unit commitment decisionmaking involving the wind generation, this paper establishes a twostage symmetric fuzzy optimization model with both fuzzy constraints and fuzzy targets. The first stage of the model determines the fuzzy parameters of the system. While, in the second stage, the actual fuzzy solution and the corresponding fuzzy level are calculated, and the uncertainty of the unit commitment is quantified.Due to the introduction of unsolved fuzzy variables, a simplified operation based on the outerpoint iteration method is proposed. In case of the dayahead prediction, the 4 h rolling prediction in the day, the 1 h ultrashort rolling prediction, the adaptability to the forecasting error of this method is analyzed though comparing with the actual situation.The results show that the fuzzy optimization can reduce the scheduling error caused by the prediction error to a certain extent, so it is suitable for the usage of system scheduling with a high uncertainty.

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蔡佳铭,王承民,谢宁,李欣.含风电电力系统机组组合问题的两阶段对称模糊建模与优化[J].电力科学与技术学报英文版,2020,35(6):36-45. CAI Jiaming, WANG Chengmin, XIE Ning, LI Xin. Twostage symmetrical fuzzy modeling and optimization for the unit commitment in wind power systems[J]. Journal of Electric Power Science and Technology,2020,35(6):36-45.

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  • Online: April 16,2021
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