Deep reinforcement learning-based integrated frequency and voltage control for isolated multi-microgrid system

The output uncertainty of distributed power source and the power disturbance caused by load pose a greater threat to the stability of isolated multi-microgrid systems. An isolated multi-microgrid load frequency controller(LFC) based on multi-agent soft actor critic(MA-SAC) algorithm is proposed,and the soft actor critic(SAC) algorithm is used to optimize and adjust the proportional integral (PI) control parameters of the automatic voltage regulator(AVR). A combined model of LFC and AVR for multi-microgrid is developed. For the design of voltage and frequency controllers,the corresponding states,action spaces and reward functions are established according to SAC algorithm and multi-agent deep reinforcement learning (MA-DRL) framework,respectively. The appropriate neural network and training parameters are selected to generate the deep reinforcement learning controller through pre-learning. Finally,through simulation analysis, the PI controller optimized based on SAC algorithm can track the voltage the reference value faster,and the MA-SAC controller can maintain the frequency stability quickly when the multi-microgrid system encounters power disturbance. © 2024 Electric Power Automation Equipment Press. All rights reserved.