The Application of Time Series Analysis To Forecasting Baghdad's Electrical Energy Production: An Empirical Study

Abstract

The behavior of time series is a significant issue in statistical sciences. Thus, forecasting power output is critical, given that energy is the lifeblood of life. Two approaches for prediction were chosen in this study: ARIMA-Box-Jenkins and Exponential Smoothing, and the two methods were compared to determine which way is the best for prediction. The actual production and predicted values were calculated using the standard of the root mean square error (RMSE). This research aims to evaluate the two approaches MAPE and MAE, and determine which one is the best for forecasting using the time series method. The findings indicate that the firm cannot produce and create power due to wars and sieges before 2003, terrorist attacks after 2003, and a lack of development plans. Additionally, the rise in population, which increases electricity demand, all of these factors contributed to a growing disparity between supply and consumption