Determining the Least Risky Solar Radiation Transposition Model for Estimating Global Inclined Solar Irradiation

Solar energy is considered one of the most important energy resources and a key component in addressing major energy challenges worldwide. Therefore, solar radiation data is crucial for many solar energy applications. Due to the lack of measurements at times due to logistical challenges, mathematical transposition models are often used to compensate for this deficiency. This paper presents an analytical study to identify the least risky transposition model for estimating solar radiation on inclined surfaces among six commonly used models in scientific literature, for several regions around the world (Berlin, Rome, Tripoli, N'Djamena, Yandou). Total horizontal solar radiation intensity data was obtained from the Solargis platform for the study regions, carefully selected to represent latitude variations and longitudinal alignment. The proposed approach was applied to these regions for six transposition models and multiple different tilt angles ranging from (90°-10°) to determine the least risky model for use in each region at each solar panel tilt angle. The study results show significant variation among the studied regions, with a notable difference in annual inclined solar radiation values between regions using transposition models, with the discrepancy increasing at higher latitudes. The results indicate that the Perez model is the least risky and dominant model in Tripoli, while in Berlin, the Liu & Jordan model was the least risky at tilt angles between 40°-10°, with the Perez model being the least risky at tilt angles greater than 40°. This study is expected to enhance the accuracy of solar radiation estimation, thus bolstering confidence in assessing the economic and environmental efficiency of solar energy systems.