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MODELING THE ELECTRICITY CONSUMPTION IN THE PROVINCE OF DAVAO ORIENTAL WITH AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE
Keywords:
seasonal ARIMA model, auto-regressive integrated moving average.DOI:
https://doi.org/10.17654/0972361722025Abstract
The inexorable ballooning population and industry had been showing a tantamount effect to the rapid increase of energy consumption worldwide. Thus, efficient energy utilization through effective management and appropriate prediction is ultimately needed for future consumption. In this study, seasonal ARIMA model was utilized in forecasting electricity consumption in the Province of Oriental using the monthly consumption from January 2004 to December 2020. Upon diagnostic checking with the use of AIC, SBC and MAPE; the ARIMA(1, 1, 0) × (0, 1, 1)12 was found to be the best fit model to do the forecasting. Results show that with the most likely prediction, there is an increasing rate of the monthly consumption with a seasonal higher demand every August. It is also forecasted that there would be nearly 49% increase of the electricity consumption in the Province from 2015 towards 2025.
Received: December 6, 2021
Accepted: January 19, 2022
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