Optimization-based performance mapping of geothermal energy-based polygeneration: Power, heating, freshwater, and compressed hydrogen production

This study evaluates a geothermal-driven polygeneration plant that couples a double-flash train with an ORC, a multi-effect distillation (MED) unit, and a PEM electrolysis plus compression pathway to co-produce net electricity, district heating, freshwater, and compressed hydrogen. A steady-state thermodynamic and exergy model is developed and validated against published PEM, MED, and ORC benchmarks. At a 180 ° C geothermal source temperature, integration increases overall efficiency from 7.20% to 36.25% (energy) and from 31.54% to 56.16% (exergy), while delivering 6000 kW net power with co-products. Global sensitivity analysis based on 5000 Latin hypercube samples and Borgonovo Delta indices shows that only 29.5% of designs satisfy steam-quality and positive net-power constraints, with net power mainly driven by resource parameters ( T 1 , m ̇ 1 ) and efficiency shaped by pressure ratios. A four-objective evolutionary optimization is then performed; NSGA-II outperforms NSGA-III (39% higher hypervolume) and extends the best random feasible performance by 24% in maximum net power. TOPSIS selects a best-compromise design delivering 15640 kW at 39.1% overall efficiency with negligible constraint-violation risk under 2% parametric uncertainty.