Use of GRA-based Taguchi approach and ANSYS simulation to optimize the performance of air-cooled solar panel

The performance of photovoltaic (PV) modules deteriorates at elevated operating temperatures, reducing efficiency and lifespan. This study experimentally investigates the application of a forced air-cooling system on a 100 W solar panel, with optimization carried out using the Taguchi method integrated with Gray Relational Analysis (GRA) and validated through ANSYS simulations. Three factors—solar flux (500–950 W/m 2 ), ambient temperature (20°C–41°C), and air velocity (1.5–6.0 m/s)—were tested at four levels. Results indicate that the optimal operating conditions (solar flux = 650 W/m 2 , air velocity = 4.5 m/s, ambient temperature = 41°C) reduced the panel surface temperature from 56.3°C to 49°C, increased power output from 83 to 92.7 W, enhanced solar efficiency from 18.1% to 21.2%, and improved exergy efficiency from 19.3% to 22.7%. The ANOVA results showed that ambient temperature had the highest contribution (≈59%) to efficiency improvements, while solar flux had the strongest influence on power output. This study fills a gap in the literature by integrating GRA-based Taguchi optimization with numerical simulations for simultaneous improvement of multiple performance indicators. The findings highlight a practical and low-cost cooling strategy that can significantly enhance PV performance in high-temperature regions or remote areas without external power requirements, showing the novelty of the present study. Graphical is shown below to indicate the same.