Two-Stage Stochastic Optimization of DC Microgrid Clusters

DC microgrid clusters (DCMGC) is a dynamic network formed by connecting a group of geographically neighboring DC microgrids (DCMGs) through tie-lines. Each DCMG collaborates with other DCMGs to achieve maximum economic benefits through flexible power flow management within the DCMG and at the system level. This paper presents a two-stage stochastic optimization (TSSO) model for the planning of DCMGC. The model takes into account the uncertainties associated with load demand and renewable energy, and minimizes the total cost of the DCMGC system as the power flow target to perform energy scheduling. According to the microgrid energy scheduling priority, the system mathematical model is used to determine the optimization objective function which is constrained according to the model, physical constraints and performance requirements. Furthermore, the power flow between DCMGC is verified by the ring topology, so as to minimize the objective function. The simulation results verify the correctness of the theoretical analysis.