Distributed Voltage Control in Smart Distribution Network based on Multi Discrete Soft Actor Critic Algorithm

The increasing ratio of renewable energy sources and the need for fast demand response of controllable power equipment have led to increasing complexity in smart distribution network control. In this paper, we propose a robust control scheme for smart distribution networks based on a multi-agent deep reinforcement learning algorithm for the smart grid voltage stability control problem. This design is deployed in two aspects. In terms of interaction environment design, considering that capacitors, regulators and distributed energy connected to a smart distribution grid have both discrete and continuous actions, the action space for interacting with agents is set to be a multidimensional discrete action space. In terms of algorithm design an intelligent active and reactive power compensation method based on multi-discrete soft actor critic (MDSAC) algorithm is proposed to realize voltage stability control. The designed MDSAC-agent is trained offline and tested online to achieve real-time smart dynamic voltage stability for smart distribution network. The proposed voltage control method is validated using the modified IEEE-13 and IEEE-34 bus systems containing controllable capacitor reactive power compensator, on-load tap changer(OLTC) and renewable energy sources. The simulation results show that the proposed method has better higher reward values and lesser voltage deviation than the other method.