A novel dual-section geothermal–parabolic trough multigeneration system for sustainable energy supply optimized via Grey Wolf Optimizer

One of the major global challenges in the energy sector is the sustainable production of electricity, freshwater, and heating with minimal environmental impact. Although renewable-based multigeneration systems have received considerable attention, integrating stable hybrid renewable sources with effective waste heat recovery remains insufficiently explored. This study proposes a novel dual-section geothermal–parabolic trough collector multigeneration system integrated with thermoelectric generators for simultaneous electricity, freshwater, and heating production. The proposed configuration combines a double-flash geothermal cycle, solar-driven parabolic trough collectors, Kalina and Organic Rankine cycles, and desalination subsystems within a dual-source structure to improve operational reliability and ensure continuous energy supply under varying conditions.In addition, thermoelectric generators are incorporated to recover thermal losses and improve overall energy utilization and system sustainability. The system combines geothermal energy and solar energy to enhance operational reliability and sustainability while utilizing thermal waste energy to improve the overall performance. Comprehensive thermodynamic, exergoeconomic, and multi-objective optimization analyses are performed to evaluate the proposed configuration. The effects of key operating parameters, including geothermal fluid mass flow rate, geothermal fluid inlet temperature, flash chamber pressures, pressure ratio, and thermoelectric generator figure of merit, are investigated. The results indicate that the system achieves energy and exergy efficiencies of 65.18% and 44.11%, respectively, with a sum unit cost of product of 6.89 $/GJ under the base operating conditions. The analyses also demonstrate that the geothermal fluid mass flow rate and inlet temperature are the most influential parameters affecting system performance. Furthermore, multi-objective optimization based on the Grey Wolf Optimizer algorithm yields optimum values of 45.15% for energy efficiency, 66.67% for exergy efficiency, and 7.39 $/GJ for the specific unit cost of product. The findings confirm that the proposed hybrid system has strong potential for sustainable and reliable energy supply in high-demand applications while reducing energy losses and environmental impacts.