Wind-Solar Energy Storage Joint System Operation Strategy Based on Multi-Objective Particle Swarm Optimization Algorithm

Through this project, our goal is to enhance the utilization efficiency of renewable resources and the operational efficiency and reliability of the power system. This study delves into the optimization of renewable energy utilization by establishing a multi-objective optimization model. This model considers the system's stability and economy, incorporating the sum of energy storage operating costs, plan deviation penalty costs, and the new energy consumption rate. Building upon this foundation, a multi-objective particle swarm optimization algorithm is employed to optimize the scheduling of wind and solar energy storage. This approach not only effectively reduces battery loss but also contributes to a reduction in overall system energy consumption. The research outcomes of this project will serve as a theoretical basis and offer technical support for optimizing the allocation of renewable energy storage, holding significant importance in advancing sustainable development.