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.