Short-Term Load Forecasting Double seasonal ARIMA Methods: An Evaluation Based on Mahakam-East Kalimantan Data

Abstract

This paper uses intraday electricity demand data from Mahakam-East Kalimantan city as the basis of an empirical comparison of univariate methods for prediction up to a day-ahead. A notable feature of the time series is the presence of both an intraday and an intraweek seasonal cycle. The forecasting methods considered in the study include: Double seasonal ARIMA modeling of the daily demand profiles. The Double seasonal ARIMA methods performed well, the method that consistently performed the best was the double seasonal.