MPC optimization control of optical-storage coupling hydrogen production system based on weight calculation
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 MATLAB-function 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.
photovoltaic hydrogen productionenergy storage systemMPCweight coefficientpower distribution