Year: 2022
Type: erratum
Abstract: The ability of bifacial photovoltaic (PV) modules to generate additional energy from the rear side makes the selection of a tilt angle more challenging than its counterpart monofacial PV. Multiple factors such as site conditions (albedo, average sun-hour ambient temperature, elevation from sea level, diffuse fraction, global horizontal irradiance, and latitude) and PV module specifications (such as bifaciality, power temperature coefficient, and efficiency) can influence the optimum tilt that ensures maximum annual yield of the bifacial PV modules. System Advisor Model (SAM) is used to generate a training dataset of optimal tilt that covers a global range of site conditions and module specifications. Furthermore, we used a Ranker-based feature selection approach to evaluate features and generate a rank-list based on their R-squared score to the dependent variable. From all the available features, the absolute latitude value, sun hour ambient temperature, global horizontal irradiance, and albedo are the most significant features. The best results offer a mathematical model to predict the optimum tilt with the lowest RMSE of 2.135° and an R2 of 0.96 given 8 site and module features.
Institution: Dubai Electricity and Water Authority
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4224253029