基于强化学习和交叉粒子群算法的电网最优潮流计算

Water Conservancy & Electric Power Machinery Pub Date : 2021-08-25 DOI:10.3969/J.ISSN.1674-1951.2021.08.011

M. Anbo, Wang Peng, Ding Weifeng, Chen Shun, Li RuDuo, Z. Zheng

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引用次数: 0

摘要

针对电力系统最优潮流计算问题,提出了一种新的基于Q学习和纵横交叉搜索的粒子群算法.改进的算法在粒子群的寻优模式中引入纵横交叉算子进行优化,加强了全局收敛能力.同时,该改进算法引入Q学习的探索模式,使其在已知的解空间内进行发掘,从而更好地平衡探索与利用之间的关系.为解决Q学习算法的维度灾难问题,使用了状态-组合动作链的方法.IEEE57和IEEE118节点系统的仿真结果表明,所提算法可以增强传统粒子群算法的全局收敛性,有效求解大规模的最优潮流问题.

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Optimal power flow calculation of power grid based on reinforcement learning and crisscross PSO algorithm particle swarm optimization

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Water Conservancy & Electric Power Machinery

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