Distributed multiple time scales energy management strategy for microgrid cluster with electric vehicles participation

A microgrid cluster is formed by interconnecting multiple microgrids, which can achieve energy complementarity and improve the utilization rate of renewable energy sources. This paper proposes a distributed multiple time scales energy management strategy for islanded microgrid cluster, which enhances the accuracy and feasibility of scheduling plans by coordinating long and short time scales. In the low-carbon economic scheduling phase at long time scale, a vehicle-to-grid (V2G) interaction model is established for incentive-based electric vehicle (EV) clusters, and a low-carbon economic scheduling model for the microgrid cluster is constructed based on model predictive control (MPC). The scheduling model is solved in a fully distributed manner using the synchronous alternating direction method of multipliers (SADMM) and a finite-time consensus algorithm. In the feedback correction phase at short time scale, the output schedule of controllable generation units is sequentially adjusted to minimize the pressure on the adjustable capacity of controllable generation units. The simulation results indicate that the proposed strategy effectively achieves low-carbon economic scheduling and reliable operation of the islanded microgrid cluster. Additionally, by optimizing the charging and discharging behaviors of EV clusters, power balance within the microgrid cluster is maintained while reducing the overall operation cost by 23.656%.