Solar Irradiation Prediction Using Weather Forecast Data

Solar radiation is an important parameter for the planning and operation of solar energy systems. Black-out occurs when the proportion of electricity that has been provided is greater or lesser than the proportion of electricity devoured. This has become an extra compound due to the hike in renewable energy, largely due to weather. Conventional power plants need to reach up to speed with these consistent variations as it is difficult to store power in enormous amounts throughout a prolonged time frame. The major objective of this work is to discover a machine learning model which accurately forecasts solar radiation. In this work, Linear Regression, ElasticNet, Gradient Boosting Regressor, Support Vector Regression, Random Forest Regressor, Extra Trees Regressor, Sequential and MultiLayer Perceptron models are used. The evaluation measures which are used in this work to identify the best model are MAE and RMSE.