Operation Optimization for Multiple Regional Integrated Energy Systems Based on Model Predictive Control under Cloud-Edge Cooperation

To make full use of the complementary potential of energy resources between different regional integrated energy systems (RIESs), this paper constructs a two-level operation optimization model under cloud-edge cooperation for multiple RIESs from the multi-level structure concept. Firstly, a real-time optimization model is built on the cloud platform of energy management to optimize the system overall economy, which meets the demand for power interaction in the day. Secondly, at each edge node, the model predictive control (MPC) is used to establish a refined energy control model based on the prediction analysis of each RIES's renewable energy generation and loads demand. Finally, the simulation verifies the feasibility of the cloud-edge coordinated control energy optimization in the real-time phase. Compared to traditional centralized control, the proposed method solves the problem of balancing the individual benefits of each RIES with the overall benefits of the system.