Different Methods for Multi-HESS Voltage Recovery in Microgrids: A Comparative Investigation

Abstract

The present study proposes two control methods in a multi-agent framework to realize the secondary voltage recovery for distributed heterogeneous energy storage systems (HESSs) in a DC microgrid. The first control method used the advanced secondary voltage recovery (SVR) control strategy. The SVR control employs a consensus-based strategy to balance the State of Charge (SoC), power, and energy across multiple HESSs to regulate the DC bus voltage despite load variations. The second control method uses an online deep reinforcement learning (DRL) algorithm called deep deterministic policy gradient (DDPG) to solve the DC bus voltage regulation by generating the control action. The simulation results show the effectiveness of these two methods and compare the advantages and disadvantages of each.