Design of Distributed Electric Power Automation Control System Based on Reinforcement Learning
This paper design scheme for distributed power automation control system based on reinforcement learning is proposed.This scheme applies reinforcement learning modeling to distributed power systems and designs state space,action space,and reward function.Then,the deep deterministic policy gradient(DDPG)algorithm is used to train the agent to autonomously adjust the control strategy based on the system state,thereby optimizing system performance.The results indicate that this scheme can effectively improve the stability,reliability,and economy of distributed power systems.
reinforcement learningdistributedautomated control
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