Two Novel Deep Learning Models for Short-term Forecasting of Solar Radiation Using Meteorological Variables

In addition to machine learning methods, deep learning is increasingly being used for solar radiation prediction. In this study, two new deep learning models with attention mechanisms are proposed, and the influence of the temporal representation on the short-term results is evaluated. To address this question, the two networks were trained on an irradiation dataset from a network of 80 meteorological stations in Galicia, Spain, with different representation intervals being simulated. The results show that, although the proposed models achieve better results in comparison to other popular models trained for the same task, the transformation performed on the data degrades the prediction ability of the models as the representation interval increases.