A Two-Phase Optimization Strategy for Enhancing the Performance of Integrated Wind-Solar-Storage Microgrid Systems

As countries worldwide adopt carbon neutrality goals and energy transition policies, the integration of wind, solar, and energy storage systems has emerged as a crucial development direction for future energy systems. In this context, this paper presents a coordinated optimization strategy for the configuration of microgrid wind-solar-storage systems, utilizing the NSGA-II algorithm and the TOPSIS evaluation method to enhance overall system performance. The study develops a power generation model, an energy storage strategy model, and a power purchasing plan model for microgrids. The optimization problem is addressed using the NSGA-II algorithm, with the objective of minimizing both electricity purchases and the curtailment of wind and solar energy. A set of Pareto-optimal solutions is generated, and the TOPSIS method is subsequently employed to rank the solutions and identify the optimal configuration. The simulation results demonstrate that this strategy significantly reduces electricity waste and lowers power supply costs, offering a novel approach for the coordinated optimization of wind-solar-storage systems.