Toussaint Tilado Guingane^{1, 2,}, Mouhamadou Falilou Ndiaye³, Sosthène Tassembedo², Éric Korsaga², Dominique Bonkoungou^{1, 2}, Zacharie Koalaga², François Zougmore²

The aim of the study was to identify the best-performing regression model for estimating the solar radiation component in Ouagadougou, Burkina Faso, a region characterised by high levels of sunshine. Of the four models evaluated, the Bristow Campbell model emerged as the optimal choice, outperforming the others in terms of accuracy. The importance of this research lies in the need to select a regression model adapted to the specific climatic conditions of the region, thus contributing to more accurate energy planning and sustainable use of solar energy. The evaluation of the models was based on metrics such as RMSE, MBE, t-statistic, R2, and the d metric, reinforced by detailed graphical visualisations and correlations between the models and real data. The results clearly demonstrated the performance of the Bristow Campbell model, underlining its reliability and efficiency in estimating global solar radiation. This conclusion is supported by an in-depth analysis of the metrics and graphs, providing valuable insights for researchers, energy planners and policy makers.

solar radiation, regression model, metrics, performance, Bristow Campbell model