Capacity Optimization and Comprehensive Benefit Analysis for Grid-Connected Hydrogen-Production Microgrid Systems

To improve the capacity of renewable energy consumption and enhance the economy of the microgrid system, this paper proposes a particle swarm optimization algorithm (PSO)-based optimization model for the capacity allocation of wind-photovoltaic-hydrogen hybrid microgrid. The model aims to maximize the system economy, and takes into account multiple economic factors such as equipment investment cost, operation and maintenance cost, power purchase and sale cost, penalty for wind and light abandonment, and compensation for load interruption, and at the same time introduces the coordinated operation strategy of hydrogen energy storage system. The PSO algorithm with dynamically adjusted inertia weights and speed constraints is used to optimize the capacity configurations of wind turbine (WT), photovoltaic (PV), electrolysis cell (EC), hydrogen storage tank (HT) and fuel cell (FC), and to establish the power balance constraints and the dynamic operation and management model of the hydrogen storage system. The simulation results show that the optimized system can achieve comprehensive economic improvement in typical scenarios, and the power abandonment rate and load interruption rate are controlled at 1.24% and 8.75%, respectively, which verifies the model's validity in coordinating economy and reliability. The study provides decision support for the planning of microgrids containing hydrogen storage with synergistic optimization of economy and reliability, which is of reference value for promoting the efficient use of clean energy.