张华赢,艾精文,汪伟.基于约束型深度强化学习的主动配电网 电压控制策略[J].电测与仪表,2023,60(5):159-166. ZHANG HUAYING,2,3.Volt/Var Control Scheme for Active Distribution Networks based on Constrained Deep Reinforcement Learning[J].Electrical Measurement & Instrumentation,2023,60(5):159-166.
基于约束型深度强化学习的主动配电网 电压控制策略
Volt/Var Control Scheme for Active Distribution Networks based on Constrained Deep Reinforcement Learning
With the access of distributed power and random load, the problem of voltage fluctuation in distribution network becomes more and more serious. Active distribution network can suppress voltage fluctuation through various voltage and reactive power controllers, but it is usually necessary to solve a complex mixed integer second-order cone programming problem, which is difficult to achieve real-time control. In this paper, a real-time voltage control model of active distribution network is established by using deep reinforcement learning, which can quickly get the control strategy satisfying the power flow constraints. First, collect node active power, node reactive power, transformer voltage regulating gear and time step as environmental state variables; secondly, coordinate the three control equipment with the cost related to network loss and equipment operation as return function; finally, solve the problem through constraint based reinforcement learning based on long-term memory network, so as to establish a real-time voltage control model of active distribution network. Based on the 4 bus test system and IEEE-33 bus test system, the simulation results show that the proposed deep reinforcement learning method can ensure the power flow constraints, and the voltage control model can control the voltage and reactive power controller in real time to ensure the voltage quality of the distribution network.
