Automatic adjustment method and device for load flow calculation convergence

The invention discloses an automatic adjustment method for load flow calculation convergence. The method comprises the steps of designing a state, an action space and a reward of a deep reinforcementlearning network for load flow calculation convergence; constructing a deep reinforcement learning ne...

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Main Authors WEN JING, GUO QIANG, CHEN XINGLEI, HUANG YANHAO, ZHANG SONGTAO, WANG TIANJING, LI WENCHEN, TANG YONG, HUANG HEKAI, WANG HONGZHI
Format Patent
LanguageChinese
English
Published 29.05.2020
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Summary:The invention discloses an automatic adjustment method for load flow calculation convergence. The method comprises the steps of designing a state, an action space and a reward of a deep reinforcementlearning network for load flow calculation convergence; constructing a deep reinforcement learning network for load flow calculation convergence according to the state, the action space and the reward; knowledge experience is added into the deep reinforcement learning network, and the process of manually adjusting the power flow is simulated, so that a power flow adjustment strategy is constructed, the power flow convergence of the power grid is adjusted by using the power flow adjustment strategy, and the problems of low convergence working efficiency, inaccuracy and overlarge manpower cost consumption of the current adjustment of the large power grid are solved. 本发明公开了一种潮流计算收敛的自动调整方法,包括:设计用于潮流计算收敛的深度强化学习网络的状态、动作空间和奖赏;根据所述状态、动作空间和奖赏构建用于潮流计算收敛的深度强化学习网络;在所述深度强化学习网络中加入知识经验,并模拟人工调整潮流的过程,从而构建潮流调整策略,使用所述潮流调整策略对电网的潮流收敛进
Bibliography:Application Number: CN202010015091