Multi-objective Search Group Algorithm for Thermo-Economic Optimization of Flat-Plate Solar Collector

This study aims to develop a multi-objective version of the search group algorithm (SGA) called the multi-objective search group algorithm (MOSGA) to help determine thermo-economic optimization of flat-plate solar collector (FPSC) systems. The MOSGA is tested on several benchmark problems and applied to the thermo-economic optimization of FPSC systems, using four different working fluids: pure water, SiO2, Al2O3, and CuO nanofluids. The results demonstrate that the MOSGA is robust and effective, achieving improvements in thermal efficiency and reductions in total annual cost compared to other optimization methods.