Abstract
Abstract The growth of solar energy infrastructure in Eastern Uganda has not consistently produced optimal levels of solar power because of a complex interplay of environmental and physical factors.In order to quantify the combined effects of crucial factors on solar power generation performance, ambient temperature, cell temperature, wind speed, and solar irradiance, this study presents an empirical model.Experimental data was collected from four operational solar power plants of Busitema, Soroti, Mayuge, and Tororo over a 215-day period by recording key parameters at 15-minute intervals. An empirical model with combined physical factors was developed and evaluated using two solar photovoltaic panels and digital technology for accurate monitoring. Available Model 1 utilizes the use of uncoupled physical factors, as compared to the developed Model 2, which combines coupled physical factors. Due to excellent wind conditions (up to 3.43 m/s), the Mayuge plant produced the most power, demonstrating that Model 2 drastically reduced the gap between design capacity (10 MW) and actual generation.The combined-factor model’s higher accuracy was confirmed by Root Mean Square Error (RMSE) findings.This study demonstrates that regionally coupled empirical modeling is essential for precise forecasts, optimal plant design, and increased solar photovoltaic (PV) system operational efficiency.The suggested approach can direct the development of solar energy infrastructure and policies in Eastern Uganda and other comparable areas across the world.