Surrogate-based optimizations of parabolic trough collectors arrays with varying geometry operating with nanofluids

Abstract Solar energy has emerged as a leading player in current scenarios promoting the decarbonization of energy matrices. Among the methods of harnessing this energy potential, concentrating collectors stand out as the most well-established technology, with the parabolic trough collector (PTC) dominating the market. Among the research efforts aimed at enhancing the heat transfer of PTCs, the dispersion of nanoparticles in heat transfer fluids (HTF) has shown improvements of up to 27% in collector thermal performance as reported in the literature. However, as a side effect, the nanoparticles result in an increase in the system’s pumping power. In this work, by using surrogate modeling, multi-objective optimizations were conducted using the NSGA-II algorithm aiming to maximize thermal efficiency and minimize pumping power in an arrangement of 8 collectors with variable geometry (including lengths, mirror widths, absorber tube diameters, and glass cover diameters) operating with two nanofluids, $${\textrm{Al}}_{2}{\textrm{O}}_{3}$$ -Syltherm 800 and Cu-Syltherm 800, at volumetric fractions between 0.1 and 5% under different irradiance conditions (500–1000 W/m $$^2$$ ), inlet temperatures (400–500 K), and volumetric flow rates (0.005–0.01 m $$^3$$ /s). Preliminary results indicated that volumetric fractions less than 0.5% allow for a reduction in pumping power of up to 3% compared to the reference collector ET-150. From the selection of geometries indicated on the Pareto frontiers, there was an increase of 1.89% in thermal efficiency for the arrangement operating under the condition of 500 W/m $$^2$$ irradiance, 500 K inlet temperature, and 0.005 m $$^3$$ /s volumetric flow rate, while the resulting pumping power was reduced by 14.9%. Furthermore, an increase in exergy efficiency of 1.74%.