Thermal-economic performance assessment of heat recovery-oriented design of integrated CCHP-H₂ system; multi-objective optimization with LCA and AdaBoost decision-making

Abstract

Combined cooling, heating, power systems integrated with hydrogen production (CCHP–H₂) can simultaneously supply useful outputs while improving the utilization of fuel and recoverable thermal energy. The present project proposes a methane-fueled CCHP–H₂ configuration integrating methane partial oxidation, a water–gas shift reactor, hydrogen separation, a gas-turbine cycle, organic Rankine cycle, steam generation, and absorption refrigeration. The system was modeled in Aspen HYSYS and assessed using energy, exergy, exergo-economic, and exergo-environmental analyses, complemented by life-cycle assessment (LCA), machine-learning (ML)-based performance prediction, and multi-objective optimization (MOO). Under the base-case conditions, the system achieved energy and exergy efficiencies of 78.28% and 66.08%, respectively, while producing 2867 kW of electricity, 2059 kW of useful heat, 294 kW of cooling, and 0.074 kg/s of hydrogen. The corresponding levelized hydrogen cost, net present value, and payback period were 7.532 USD/kgH₂, 19.763 million USD, and 2.09 years, respectively. The specific CO₂ emission and global warming potential were 0.2312 kg CO₂ /kWh and 4317.7 kg CO₂ /h, respectively. The optimized ML–MOO–TOPSIS solution increased exergy efficiency to 70.67% and reduced specific CO₂ emissions to 0.214 kg CO₂ /kWh while lowering the selected economic objective. These results indicate that the proposed configuration can provide effective heat recovery and integrated polygeneration under the assumed operating and economic conditions. Nevertheless, the results are based on steady-state process simulation and system-level assumptions for selected components; therefore, detailed equipment design, experimental validation, site-specific LCA, and dynamic and uncertainty-aware analyses are needed to assess practical deployment and performance under variable operating conditions.