This study introduces an optimized hydrogen liquefaction process using an enhanced precooled Joule-Brayton cycle. Hydrogen liquefaction is highly energy-intensive due to the cryogenic temperatures required, and its efficiency improvements are limited ...
This study introduces an optimized hydrogen liquefaction process using an enhanced precooled Joule-Brayton cycle. Hydrogen liquefaction is highly energy-intensive due to the cryogenic temperatures required, and its efficiency improvements are limited by the process complexity, capital costs, and technical risks. To address these challenges and harness the environmental benefits of hydrogen as a future energy source, we propose a novel optimization approach by analyzing the sensitivity of the objective function to key process variables. This method reduces the total cost by balancing equipment costs and energy consumption. The optimization is conducted through an integrated MATLAB-Aspen HYSYS framework using a Genetic Algorithm (GA). A thermodynamic analysis, accounting for non-ideal operations, is carried out based on the composite curves of heat exchangers and the entropy of the cycle. The process liquefies 5 tons of hydrogen per day, achieving a specific energy consumption (SEC) of 5.941 kWh/kg, a coefficient of performance (COP) of 0.2065, and a figure of merit (FOM) of 0.5125, showing better performance than recent studies. Exergy analysis reveals an efficiency of 51%, significantly higher than that of similar processes. The economic analysis estimates the levelized cost of hydrogen (LCOH) to be $3.42/kg. These results provide practical insights into the optimization and economic feasibility of hydrogen liquefaction processes.