A two-stage cloud-edge optimization scheduling strategy for distributed energy in microgrids

Abstract With the widespread access to distributed energy, the information interaction and computing scale of microgrid scheduling have greatly increased. Given the limitation that existing research ignores the coupling of computing delay and user response, a two-stage optimization strategy for microgrid cloud-edge is proposed. A scheduling model with economic optimization as the goal is constructed, the day-ahead-real-time hierarchical optimization and computing offloading mechanism are introduced, and the model is converted into a multi-parametric quadratic programming (MPQP) problem for solution. Simulation results show that the proposed method has good effects in reducing computing delay and scheduling cost, and can effectively improve the system operation efficiency.