Solar energy forecasting: A comparison on Regression and Artificial Neural Network models

The continuous use of energy is the main reasons for the integration of solar energy into the electric grids. In solar power plant the power output is based on incoming radiation. That’s why for the operators of grid and other decision makers it is necessary to find that how much power will be produced by the solar plant in next hour or day. The information obtained by forecasting is very important or necessary for efficient grid operation and also for solar energy trading. This study deals with a detailed analysis of techniques which are used for solar energy forecasting and their comparison on same data set. These models helps in finding the suitable forecast method as per the requirements.