Investigation of Transformer-based models performance on solar irradiance forecast: Empirical results and analysis

Solar irradiance forecasting is of paramount importance in the efficient management of renewable energy systems. Transformer-based models have garnered substantial interest in this field due to their exceptional scalability and performance. However, the influence of various factors, such as temporal scales, regional disparities, and weather conditions, on their forecasting capabilities remains an underexplored area. To elucidate the inherent strengths of Transformers and their variants in irradiance forecasting, an exhaustive assessment of the Transformer and its derivatives is proposed, employing the most recent models. Nine models, including the Transformer and its eight enhanced versions, are compared across short-term, mid-term, and long-term tasks using data from two public databases in three distinct regions. The evaluation encompasses various performance metrics and diverse weather…