The article discusses the importance of transitioning to a new energy system by developing renewable energy sources like wind, solar, and hydrogen storage. It introduces an optimization model for a wind-solar-hydrogen storage system aimed at reducing overall system costs and enhancing environmental protection. The model incorporates an advanced multi-objective particle swarm optimization algorithm with varying learning factors and exponential nonlinear decreasing inertia weight. By optimizing the model using the IMOPSO algorithm, the total cost and environmental protection cost are minimized to 8262 CNY/(kW·h) and 541.9 CNY/(kW·h) respectively. The integration rates of wind and solar power reach significant levels, showing an increase compared to traditional algorithms. The system achieves a clean energy supply rate of 94.1%, providing a novel approach to storing and utilizing clean energy. The article also highlights various studies in the field of multi-energy complementarity, emphasizing the importance of integrating wind, solar, and hydrogen storage systems for sustainable energy production.