Abstract—The electricity demand has been steadily increasing throughout the years. A robust predictive model is required to prepare for future electricity consumption. This paper applied the ARIMA models to forecast electricity consumption in the Philippines. Dataset used was retrieved from the Philippine Institute for Development Studies website. It contains 48 data points, of which 43 were used in model building, and the remaining 5 data points were used in forecast evaluation. The order of the ARIMA (p,d,q) model was based on the ACF and PACF plots. The model with the most negative AIC value was chosen among the candidate models, and the best-fitting model was identified. Based on the analysis results, ARIMA (0,2,1) is the statistically appropriate model to forecast electricity consumption in the Philippines. It is predicted that by 2030, the Philippines will consume 163,639.9 GWh of electricity. The R statistical software was used to do all of the calculations.
Index Terms—ARIMA, electricity consumption, time series forecasting.
S. J. E. Parreño is with the University of Mindanao Digos College, Philippines (e-mail: samueljohnparr@gmail.com).
Cite: Samuel John E. Parreño, "Forecasting Electricity Consumption in the Philippines Using ARIMA Models ," International Journal of Machine Learning and Computing vol. 12, no. 6, pp. 279-285, 2022.
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