Solar Irradiation Prediction Level

Abstract

The discipline of Machine Learning (ML), a branch of Artificial Intelligence, enhances the ability to model crucial variables for generating green energy, such as solar radiation. Precise prediction of solar irradiation assists in the strategic placement of solar panels, optimizing energy production, reducing reliance on non-renewable energy sources, and promoting environmental conservation. This research aimed to develop a model for predicting solar irradiation using the Multiple Linear Regression (MLR) technique. The results, while indicating a moderate performance (R²=0.56, MAE=158.23, MSE=43804.89, and RMSE=209.29), provide a valuable starting point for future studies that seek to improve accuracy with more advanced techniques, such as artificial neural networks (ANN) or hybrid models. This research emphasizes the importance of continuing to investigate more sophisticated models for more accurate prediction and suggests that linear models, while useful for understanding basic relationships, have limitations that can be overcome with more advanced approaches.