Solar Radiation Prediction Using Regression Methods

Solar irradiation forecasting is becoming an important technique in load demand management due to recent developments in modern society and the economy. Accurate prediction of produced solar power can aid in estimating the size of the system, load measurement of the system, and calculating return on investment (ROI). For estimating solar irradiance at any geographical location, various methods can be employed such as averaging solar irradiance. For predicting irradiance, different regression techniques have been applied. This paper performed a comparison between the regression methods such as Multiple Linear Regression (MLR), Random Forest Regression (RFR), and Gradient Boosting Regression (GBR) methods and examines the efficient method for forecasting solar irradiance.