A Distributed Deep Reinforcement Learning Approach for Reactive Power Optimization of Distribution Networks
An actor-critic based distributed deep reinforcement learning approach is proposed to optimize the reactive power of the distribution network under the access of distributed photovoltaics, wind turbines and other power sources.This approach can optimize and dispatch the resources of the distribution network in real time under the change of non-meta