Thermal performance analysis of parabolic trough collector (PTC) with genetic algorithm-driven multi-objective optimization under free-molecular conduction effects in the evacuated annulus

Abstract This study presents a thermal performance analysis of a parabolic trough collector (PTC) system through the coupling of a detailed thermal model with a genetic algorithm-driven multi-objective optimization framework. The core methodological contribution lies in the simultaneous optimization of thermal efficiency, heat loss, and pumping power, accounting for free-molecular conduction effects in the evacuated annulus. The analysis shows that incidence angle and mirror reflectance significantly govern optical efficiency, while rising fluid temperature drives radiative losses and reduces global efficiency. Higher direct normal irradiance (DNI) consistently improves collector performance. The multi-objective optimization using a genetic algorithm with a population of 1000 over 500 generations, generates a Pareto front that reveals clear trade-offs among the three objectives, with optimal solutions favoring high optical efficiency, mirror reflectance, and receiver absorptance.