Design optimization and performance comparison of green hydrogen production via PEM, alkaline, and solid oxide electrolyzers coupled with a geothermal power system

Integrating renewable energy sources with various electrolyzer technologies presents a flexible and promising route toward achieving green hydrogen production and supporting net-zero emission goals. This study conducts a parametric investigation and multi-objective optimization of hydrogen generation using three types of electrolyzers—proton exchange membrane (PEME), alkaline (AE), and solid oxide (SOE)—in combination with a geothermal power generation system. Because the SOE requires high operating temperatures, a solar plant is incorporated to preheat the water before it enters the electrolyzer, and the output power of the geothermal plant is supplied to the electrolyzer for hydrogen production in all configurations. The main feature of this study relies on considering key operational parameters, including temperature, current density, and electrolyte thickness, which are examined to assess their influence on system efficiency and cost performance. Then, a combination of artificial neural networks and genetic algorithms is employed to optimize energy, exergy, and exergoeconomic outcomes. The results show that the SOE-based configuration achieves the highest exergy efficiency, reaching 18.23%. In terms of economic performance, the AE system is the most cost-effective, with a total cost rate of 19.84 $/h and a hydrogen production cost of 11 $/GJ (1.32 $/kg). These results underscore the efficiency–cost trade-offs and provide guidance for optimizing geothermal-integrated hydrogen production systems.