电气传动2026，Vol.56Issue(3)：81-87,7.DOI:10.19457/j.1001-2095.dqcd26592
基于改进SAC算法的微电网优化调度
Optimal Scheduling of Microgrid Based on Improved SAC Algorithm
雷强 1武鹏荣 1李振文1
作者信息
- 1. 西安工程大学电子信息学院,陕西 西安 710600
- 折叠
摘要
Abstract
In response to the intermittency and uncertainty of wind power generation,which result in low wind power utilization and high electricity purchase costs in microgrids,an intelligent dispatch strategy based on a residual-like soft actor-critic(R-SAC)algorithm was proposed.The scheduling problem was formulated as a partially observable Markov decision process(PO-MDP),and short-term predictions of wind power output and load variations were achieved by combining long short-term memory(LSTM)networks with the attention mechanism.A residual-like network structure was then incorporated into the traditional soft actor-critic(SAC)framework to construct an improved R-SAC algorithm,which enhanced the convergence speed and exploration efficiency of the policy.Finally,simulation experiments based on data from an actual microgrid in the northwest region validated the effectiveness and superiority of the proposed strategy.关键词
微电网调度/风电消纳/深度强化学习/状态估计/策略网络优化Key words
microgrid scheduling/wind power utilization/deep reinforcement learning(DRL)/state estimation/policy optimization分类
信息技术与安全科学引用本文复制引用
雷强,武鹏荣,李振文..基于改进SAC算法的微电网优化调度[J].电气传动,2026,56(3):81-87,7.
