This paper proposes a multi-agent deep reinforcement learning-based approach for distribution system voltage regulation with high penetration of photovoltaics (PVs). The designed agents can learn the coordinated control strategies from historical data through the counter-training of local policy networks and centric critic networks. The learned strategies allow us to perform online coordinated control. Comparative results with other methods show the enhanced control capability of the proposed method under various conditions.

中文翻译：

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使用协调光伏逆变器的基于多智能体深度强化学习的电压调节

本文提出了一种基于多智能体深度强化学习的方法，用于具有高渗透率的光伏（PV）配电系统电压调节。设计的代理可以通过本地策略网络和中心评论网络的反训练从历史数据中学习协调控制策略。学习到的策略使我们能够执行在线协调控制。与其他方法的比较结果表明，该方法在各种条件下的控制能力增强。