Application of Analytics using R Programming for Forecasting Day-ahead Electricity Demand

Analytics technologies are becoming increasingly important for the organizations to mine and get insights into large amount of structured and unstructured data, and also to enable effective decision making for the management. One of the challenges for power industry is to estimate the Day-ahead power demand specifically to predict the peak and low demand periods. In this paper, the modeling techniques of analytics for forecasting are discussed. This paper investigates application of ARMA and GARCH modeling techniques to fit the historical data and estimate the coefficients to predict the Day-ahead electricity demand. R-Programming is used to fit the models.