Comparative Analysis of Different Models within RadEst 3.0 for Solar Radiation Estimation at Dhankutta, Nepal

To develop efficient solar energy technologies, it is essential to understand accurately the distribution of solar radi- ation in each geographical location. This research project estimates total solar radiation reaching a surface daily in Dhankutta (26.983°N, 87.346°E, 1192 m), Nepal by utilizing weather data including temperature, humidity, wind speed, rainfall, and measured solar radiation data. Four distinct models (Bristow-Campbell (BC), Campbell-Donatelli (CD), Donatelli-Bellocchi (DB), and Donatelli-Campbell-Bristow-Bellocchi (DCBB)) were employed to estimate global solar radiation (GSR). Root mean square error (RMSE), coefficient of residual mass (CRM), mean bias error (MBE), mean percentage error (MPE), and coefficient of determination (R2 ) were among the statistical tools used to assess the effectiveness of models. By minimizing RMSE, and CRM, and maximizing R2 , parameter fitting (PF) is used to calibrate all four models. The annual mean daily GSR for 2021 and 2022 was determined to be 14.5 ± 0.25 MJ/m2/day and 15.7 ± 0.24 MJ/m2/day, respectively, indicating sufficient potential for solar energy generation. The maximum GSR of 37.6 MJ/m2 /day and 26.5 MJ/m2 /day were observed in 2021 and 2022 respectively. Among the four models used to estimate GSR, the CD model showed the highest accuracy with an R2 value of 0.60 so the CD model is considered the most reliable method for predicting GSR levels in this area.