Forecasting electrical power consumption using ARIMA method based on kWh of sold energy

Abstract

Customer demand for electrical energy continues to increase, so electrical energy infrastructure must be developed to fulfill it. In order to generate and distribute electrical energy cost-effectively, it is crucial to estimate electrical energy consumption reasonably in advance. In addition, it is necessary to ensure that customer demands can be met and that there is no shortage of electricity supply. This study aims to determine the estimated long-term electricity use with a historical Energy Sold (T1) database in kW accumulated over several periods from 2008 to 2017. The ARIMA method with the Seasonal-ARIMA (SARIMA) pattern is used in forecasting analysis. The ARIMA method was chosen because it is considered appropriate for forecasting linear and univariate time-series data. The results of this study indicate that the MAPE (%) error rate is relatively low, with a result of 7,966, but the R-Square reaches a value of -0.024 due to the lack of observational data.