A grid-connected wind-solar hydrogen production system is investigated.To reduce the levelized cost of hydrogen

mitigate wind and solar power curtailment

and control the initial investment

a capacity optimization model based on an improved multi-objective particle swarm optimization algorithm is proposed.The optimization objectives are to minimize the levelized cost of hydrogen

the wind and solar curtailment rate

and the initial investment.In addition to conventional operating constraints

grid-interaction constraints and hydrogen-supply reliability constraints are incorporated into the model.A dynamic hydrogen-supply regulation strategy based on hydrogen storage state feedback is also proposed.Under this strategy

the hydrogen-supply flow rate is dynamically adjusted according to the electrolyzer power and the hydrogen storage level

while the operating priorities of the electrolyzer and battery energy storage system are optimized according to time-of-use electricity prices.An improved multi-objective particle swarm optimization algorithm is employed

incorporating an adaptive penalty mechanism and dynamic parameter adjustment to enhance constraint-handling capability and convergence performance.The case study results have verified the effectiveness of the proposed optimization model.