Multi-Objective Optimization and Techno-Economic Comparison of CSP-sCO2-Cu-Cl and PV-PEM Systems for Solar Hydrogen Production

There is a need to identify cost-effective and efficient pathways for solar-driven hydrogen production, as existing analyses often assess individual technologies in isolation and lack consistent comparative frameworks. Thus, this study conducts a techno-economic comparison and multi-objective optimization of two production pathways, (1) a concentrated solar power (CSP) system integrated with a supercritical CO2 (sCO2) Brayton cycle and a copper-chlorine (Cu-Cl) thermochemical cycle, and (2) a photovoltaic (PV) system coupled with a polymer electrolyte membrane (PEM) electrolyzer. Two CSP receiver configurations, particle-based and gas-based, are evaluated to assess the influence on system performance. A multi-objective optimization framework using the NSGA-II algorithm is applied to minimize the levelized cost of electricity (LCOE) and hydrogen (LCOH2) while maximizing system efficiency. Cost uncertainty is addressed using Latin Hypercube Sampling with AACE Class-5 uncertainty ranges. Results based on mean values from the uncertainty analysis show that the optimized particle-based CSP system achieved LCOH2 of $4.13/kg (5th − 95th percentile:$2.39-5.87/kg) and LCOE of 0.064/kWh ($0.059-0.069/kWh), with an efficiency of 19.8%. The gas-based CSP system yields LCOH2 of $4.87/kg ($2.93-6.80/kg) and LCOE of $0.091/kWh ($0.074-0.11/kWh), with an efficiency of 20.6%. In contrast, the optimized PV-PEM system exhibits a higher LCOH2 of $6.34/kg (5.58-7.08/kg) and a lower efficiency of 9.6%.