Distributionally Robust Economic Dispatch Strategy for High-Penetration Photovoltaic Microgrids Considering Generation-Load Uncertainty

As the penetration of renewable energy increases, microgrid optimization scheduling faces challenges due to uncertainty in both renewable energy generation and load demand. This paper proposes a Distributionally Robust Optimization (DRO) method to enhance the economy and reliability of high-penetration photovoltaic (PV) microgrids. An optimization model with day-ahead and real-time stages is developed to minimize operating costs, including purchase/sale costs, fuel costs for controllable generation, transmission line fluctuation penalties, energy storage losses and maintenance, and demand response costs. Uncertainty is modeled using ambiguity sets based on Wasserstein distance, and the Column and Constraint Generation (C&CG) algorithm is used for solving. Numerical results show that DRO reduces operating costs and improves the system’s adaptability to uncertainty, providing an effective strategy for high-penetration PV microgrid scheduling.