Zhang Zhi1, Haiyu Huang2, Wei Xiong2, Yijia Zhou3, Mingyu Yan3,*, Shaolian Xia2, Baofeng Jiang2, Renbin Su2, Xichen Tian4
Energy Engineering, Vol.121, No.6, pp. 1557-1576, 2024, DOI:10.32604/ee.2024.047401
- 21 May 2024
Abstract Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existing scenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios, which threatens the robustness of stochastic unit commitment and hinders its application. This paper provides a stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming and Benders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouples the primal problem into the master problem and two types of subproblems. In the master problem, the committed generator is determined, while the feasibility and… More >
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