Enhancing energy efficiency with a photovoltaic-based multi-product system with integration of electrolysis and desalination

Abstract Photovoltaic (PV)-based multi-product systems are the most effective strategies for optimizing energy consumption and enhancing energy production efficiency, which integrates multiple energy production processes within a single framework for maximizing the utilization of available energy. This research aims to provide an inclusive analysis of the PV-based multi-product system performance, which integrates electrolysis, and desalination units for simultaneous generation of power, hydrogen, and freshwater. Therefore, the optimized Extreme Gradient Boosting (XGBoost) model was carefully developed and trained to ensure high levels of accuracy and precision in predicting the power, fresh water, and hydrogen outputs of the system under varying operational conditions. This optimized XGBoost model is achieved through the hyperparameter tuning by the HenryGas Solubility Optimization Algorithm, which ensures high levels of accuracy and precision. The day-by-day analysis of power and hydrogen generation demonstrated that in winter, a minimum PV power of 6,200 kW and a hydrogen mass flow rate of 65 kg were witnessed due to low solar radiation and short daylight hours. In contrast, summer and spring registered the highest PV power levels of 8,000 kW and 7,500 kW, respectively, and hydrogen mass flow rates of 75 kg due to high solar radiation and prolonged daylight hours, hence enhancing system performance.