Optimization using RSM of combined cycle of power, NG, and hydrogen production by a bi-geothermal energy resource and LNG heat sink

This study presents a comprehensive optimization of a tri-generation system that integrates dual geothermal wells, Liquefied Natural Gas (LNG) cold energy recovery, and hydrogen production using an advanced Response Surface Methodology (RSM) approach. The system combines two geothermal wells with different temperature profiles, power generation via an Organic Rankine Cycle (ORC), and hydrogen production through a Proton Exchange Membrane (PEM) electrolyzer, enhanced by integrated LNG regasification for improved energy recovery. The primary novelty of this work lies in the first application of RSM for multi-objective optimization of geothermal-based tri-generation systems, moving beyond the conventional single-objective approaches. A 40-run experimental design is employed to simultaneously optimize three critical performance indicators: exergy efficiency, power-specific cost, and hydrogen production rate, considering six key operating parameters. The RSM framework enables systematic exploration of parameter interactions and delivers statistically validated predictive models, offering a robust and computationally efficient optimization strategy. The optimized system achieves outstanding performance, with an exergy efficiency of 44.60%, a competitive power-specific cost of 19.70 $/GJ, and a hydrogen production rate of 5.15 kg/hr. Comparative analysis against prior studies confirms the superiority of the RSM-based approach, demonstrating a 1% improvement in exergy efficiency (44.60% vs. 44.16%), a significant 44.1% increase in hydrogen production rate (5.15 kg/hr vs. 3.575 kg/hr), and a 0.81% reduction in power-specific cost compared to genetic algorithm-based optimization.