电力系统及其自动化学报2025，Vol.37Issue(2)：78-88,11.DOI:10.19635/j.cnki.csu-epsa.001469
基于深度强化学习的光伏主动配电网暂态电压控制
Transient Voltage Control of Photovoltaic Active Distribution Network Based on Deep Reinforcement Learning
摘要
Abstract
To solve the problem of transient voltage drop after grid fault which is caused by the access of a large quantity of power electronic equipment,a transient voltage control strategy for photovoltaic(PV)active distribution network based on deep reinforcement learning is proposed.First,the inherent relationship between the reactive power output ca-pacity of a PV inverter and the AC-side voltage and active power under transient voltage drop is analyzed,and an explic-it expression for the short-term reactive power output from the PV inverter is established.Then,a deep deterministic policy gradient algorithm is further used to optimize the inner-loop control parameters of the PV power output,so that the PV inverter can adjust its active and reactive power output according to the grid voltage drop.To improve the re-sponse speed of transient reactive power,a flexible switching mechanism of transient/steady-state control strategy is de-signed,so that the PV inverter can quickly inject reactive power to support the grid voltage during the voltage drop by means of single closed-loop control.Finally,the effectiveness of the proposed control strategy is verified by the compari-son of numerical examples through simulations.关键词
光伏发电/主动配电网/暂态电压/深度强化学习/电压支撑Key words
photovoltaic(PV)power generation/active distribution network/transient voltage/deep reinforcement learning/voltage support分类
信息技术与安全科学引用本文复制引用
宋晓喆,孙剑英,付小标,王长江,王鼎..基于深度强化学习的光伏主动配电网暂态电压控制[J].电力系统及其自动化学报,2025,37(2):78-88,11.基金项目
国网吉林省电力有限公司科技项目(SGJL0000DKJS2200369). （SGJL0000DKJS2200369）
