Key Optimization Technologies for Multi-Energy Integrated Supply Systems in Large Ports
This study addresses the high operational costs and low renewable penetration in large ports by proposing a multi-energy integrated supply system that coordinates wind, solar, hydrogen, battery storage, and grid electricity. A mathematical model is formulated to minimize electricity cost, and particle swarm optimization (PSO) is employed to schedule energy resources and flexible loads. Using measured data from a typical spring day at a port, two scenarios are evaluated: one without flexible load consideration and one with flexible load participation. Results show that compared to grid-only supply, the optimized system reduces electricity cost by 32.60% and 37.73% for the two scenarios, respectively, while increasing the clean energy utilization ratio by 55.46% and 58.54%. The integration of flexible loads further enhances peak shaving and valley filling, improves dynamic response, and optimizes the power consumption structure. The findings validate the feasibility and practicality of the proposed multi-energy integrated supply system for large ports, offering a viable pathway for decarbonizing port operations and achieving dual-carbon goals.