Probabilistic Forecasting Analysis on Electric Load Systems

The clustering process is the prime key to organize and analyse data mining and big data analytics. Electric load generation and electric load consumption are considered as variables and that are studied through some statistical techniques. The important techniques which are used in this work are correlation, bivariate analysis, regression analysis, semi-average method and ARIMA model. The required results including the fitted Regression model, ARIMA model and forecasted values are obtained. Electric consumption charges are discussed.