Time Series Analysis of Electricity Consumption Forecasting Using ARIMA Model

Power consumption is a very important factor in smart grids for load management process. Forecasting energy consumption is the first step in dealing with load management. For forecasting time series, the ARIMA models are one of the widely used models which showing encouraging results. In this study, ARIMA models were proposed to predict future electricity consumption. The ACF and PACF plots were used as well as stationarity of the data to identify (p, d, q) values. The results showed the accuracy and efficiency of the models and their ability to compete with current techniques for forecasting electricity consumption based on the use of the Mean Absolute Percentage Error (MAPE) to measure the accuracy of the prediction, as the model was able to predict with an error of 4.332%.