Optimal Scheduling of Water-Wind-Solar-Storage Complementary System Based on Particle Swarm Optimization

This paper proposes an optimal scheduling algorithm based on particle swarm optimization (PSO) for a water-wind-solar-storage complementary system. The goal is to enhance the utilization of hydropower, wind, and solar generation while mitigating output volatility during grid integration. The output model for the system is established, with constraints and output equations for hydropower, wind, solar, and pumped storage. The total output power fluctuation is chosen as the objective function. An improved PSO algorithm is applied to optimize the system. The results demonstrate that the proposed method significantly increases renewable energy absorption and reduces the grid impact of multiple energy sources when integrated, confirming its robust optimization performance.