基于深度强化学习的电网调控安全风险控制策略

Strategy of Security Risk Control of Power Grid Regulation Based on Deep Reinforcement Learning

阐述电网调控运行中的数据采集、安全风险特征选择、基于深度强化学习的电网切机决策控制,提出一种全新的控制方法。探讨在实际应用中可有效降低发电机的运行速度偏差,促进高精度调控。

This paper describes the data acquisition,security risk feature selection,power grid outage decision control based on deep reinforcement learning in power grid regulation and operation,and proposes a new control method.It discusses how to effectively reduce the speed deviation of the generator and promote high-precision regulation in practical application.