Reactive Power Optimization for Voltage Stability in Energy Internet Based on Graph Convolutional Networks and Deep Q-learning

The rapid response of reactive power compensation is crucial to guarantee the stable operation of energy Internet (EI) with variable loads and distributed power generations. Therefore, this paper proposes an intelligent approach for reactive power optimization in EI based on graph convolutional networks (GCN) and deep Q-learning (DQN). With the adjacency matrix that represents topology of EI, the ...