Optimization control strategies for hydrogen production system coupled with photovoltaic and energy storage are studied

and a power allocation strategy based on model predictive control that considers multi-objective optimization problems with game relationships is proposed. Firstly

the architecture of the hydrogen production system coupled with photovoltaic and energy storage is constructdd

and the power balance equation that needs to be met during the operation of the hydrogen production system coupled with photovoltaic and energy storage is clarified. Secondly

a composite algorithm model is established by combining the self-adaptive multi-objective particle swarm optimization algorithm with the MPC algorithm

and three objective functions that consider both alkaline electrolyzer(AEL) and energy storage battery characteristics are provided

then the weight coefficients of the optimal control increment are calculated. Finally

the MPC controller model is constructed using the MATLABfunction module

and the calculated weight coefficients of the optimal control increment are applied to the MPC optimization process

thus the online power allocation for the hydrogen production system coupled with photovoltaic and energy storage is ultimately achieved. Through simulation analysis and comparison with two optimization control methods

it is proven that the proposed method in this paper improves the operational indicators of the energy storage system to a certain extent while reduces the fluctuation of AEL input power

it enhances the dynamic power balance ability of the hydrogen production system coupled with photovoltaic and energy storage.