Hydrogen Production From a PV/PEM Electrolyzer System Using a Neural-Network-Based MPPT Algorithm

The electrolysis of water using a polymer electrolyte membrane (PEM) electrolyzer is a very vital and efficient method of producing hydrogen (H₂). The performance of this method can be significantly improved if a photovoltaic (PV) array, with maximum-power-point (MPP) tracker, is utilized as an energy source for the electrolyzer. This paper suggests a stand-alone PV/PEM electrolyzer system to produce pure hydrogen. The paper also develops the different mathematical models for each constituent subsystem. Moreover, the paper develops the suitable maximum-power-point tracking algorithm that is based upon utilizing the neural network. This algorithm is utilized together with the action of the PI controller to improve the performance of the suggested stand-alone PV/PEM electrolyzer system through maximizing the hydrogen production rate for every instant. Finally, the suggested hydrogen production system is simulated using the Matlab/Simulink and neural network toolbox. The simulation results of the system indicate the improved relative performance of the suggested hydrogen production system compared with the traditional case of direct connection between the PV array and the PEM electrolyzer.