ARIMAX models for predicting electrical energy consumption in Samawah city
In this paper, the aim was to develop an ARIMAX model to predict electricity consumption until 2030 using the population growth rate as an external variable (X) in the city of Samawah. The proposed models were compared, and the best prediction model was selected based on the Mean Average Percent Absolute Error (MAPE) criterion. Therefore, forecasting performance is improved by taking into account these important factors dependent on electricity consumption. The predicted results indicate that the proposed model is more accurate according to the mean absolute percentage error (MAPE) obtained during the model testing period. Given the availability of historical load data on utility databases, research is underway in the field of time series modeling for electricity load forecasting. Forecasting electricity consumption helps improve performance and accurate planning to determine the amount of energy a city needs.
Keyword: ARIMAX, Forecasting, population growth & MAPE
