Akademik Veri Yönetim Sistemi
Fuel, cilt.426, 2026 (SCI-Expanded, Scopus)
This study presents a dual tri-objective optimization of a solar-powered multigeneration system for the simultaneous production of liquid hydrogen, freshwater, and electricity. In the first optimization scenario, the objective functions are defined as maximizing overall exergy efficiency, maximizing annual hydrogen production rate, and minimizing total cost rate, while the second scenario aims to maximize freshwater production and net power generation and simultaneously minimize total cost rate. The integrated configuration comprises parabolic trough collectors, thermal energy storage, reverse osmosis desalination, a Claude liquefaction cycle, a high-temperature cascaded organic Rankine cycle (ORC), and alkaline water electrolysis, modeled under dynamic 24-hour solar conditions. A Genetic Algorithm (GA) is employed for multi-objective optimization, while an Artificial Neural Network (ANN) is developed as a surrogate model to approximate system outputs and significantly reduce computational time during the optimization process. Eighteen material configurations are systematically evaluated by examining two phase change materials (NaBr–MgBr2 and Li2CO3–Na2CO3–K2CO3), three nanofluid-based heat transfer fluids (AlN, ZnO, and TiC), and three ORC working fluids (Isopentane, Cyclohexane, and n-Octane). Results indicate that material selection is the dominant driver of thermo-economic performance, with a strong correlation between nanofluid thermal conductivity and economic viability. The configuration employing AlN nanofluid, Cyclohexane, and NaBr–MgBr2 PCM consistently dominates the Pareto frontier in both optimization scenarios, achieving a maximum Net Present Value of $16.15 million with a payback period of 1.56 years, an exergy efficiency of 25.24%, annual hydrogen production of 52.58 million kg, freshwater generation of 643.05 million kg/year, and 1,047 kW of net power output. Multi-criteria decision-making methods (TOPSIS, PROMETHEE, and VIKOR) confirm the robustness of this best-compromise solution. The findings demonstrate that minimizing exergy destruction through optimized nanofluid–organic fluid combinations yields substantial techno-economic gains, providing a scalable pathway for resilient large-scale green fuel and resource production. The proposed integration achieves a 25.24% exergy efficiency and 75.01% energy efficiency, representing a 15–20% improvement over conventional hydrogen liquefaction systems. It reduces the specific liquefaction energy to 5.73 kWh/kg LH2, compared to the typical 7–9 kWh/kg LH2 of traditional Claude cycles. The system also demonstrates a NPV of 16.15 million $ and a 1.56-year payback period, outperforming conventional systems, which have longer payback periods (4–6 years) and lower NPVs.