Evaluation of High-Efficiency Hydrogen Production from Solar Energy using Artificial Neural Network at the Université du Québec à Trois-Rivières

Hydrogen produced through renewable energy sources is rapidly emerging as one of the most promising ways to meet future fuel demands. Developing models that simulate the operation of this process (photovoltaic (PV) panel, electrolysis devices, etc.) is paramount to efficiently designing power generation systems, cutting manufacturing costs, and reducing resource usage. Artificial Neural Network (ANN) plays a crucial role in developing predictive models for complex systems due to their nonlinear nature. This study evaluates the solar hydrogen production in Trois-Rivières while modeling the PV by ANN and the water electrolysis process using semi-empirical equations. According to the obtained results, solar panels can be used for the annual production of more than two thousand and seventy hundred lig of hydrogen in UQTR.