Employing cooling/power cycle in a sustainable geothermal scheme integrated desalinated water-based H₂ production/liquefaction; AI-aided multi-facet optimization and economic examination

The sustainable nature of geothermal energy, combined with advances in power generation technologies, has allowed establishing sustainable energy supply programs. To respond to significant thermal losses, it is crucial to develop hybrid systems that minimize irreversibility through environmentally friendly methods, which is vital for the longevity of these energy conversion processes. Thus, this study introduces an innovative environmentally friendly thermal plan that identifies and addresses points of thermal losses in a geothermal power cycle. The process employs a multi-step approach for producing desalinated water, converting it into hydrogen, and subsequently liquefying hydrogen gas. The suggested scheme incorporates subsystems, encompassing a geothermal flash cycle, an organic flash cycle, a unit for thermally produced desalinated water, a combined cooling and power cycle, a water electrolysis module, and a Claude cycle. This research assesses the thermodynamic, cost, and sustainability viewpoints. The research's primary aim is to optimize the system's performance using an artificial intelligence-driven optimization algorithm. The optimization targets the cost of liquefied hydrogen and exergy efficiency as objective functions, employing artificial neural networks that achieve a regression coefficient of 1 to initiate the optimization process. Using the NSGA-II algorithm, four decision variables are utilized to map the Pareto front, revealing an optimum exergetic efficiency of 0.3208 and a liquefied hydrogen cost of 0.3676 $/lit. The hydrogen liquefaction rate is attained at 44.57 lit/h, resulting in a sustainability index of 1.472.