Electricity load demand forecasting using exponential smoothing methods

Abstract

In this paper five exponential smoothing methods are considered for load forecasting for lead times from a half-hour-ahead to a year-ahead. Forecasting load demand with high accuracy is required to prevent energy wasting and system failure. For this purpose, a half-hourly load demand of Malaysia for one year, from September 01, 2005 to August 31, 2006 was used. The mean absolute percentage error (MAPE) is used for comparing the forecasting accuracy. Time series of load demand recorded at half-hourly intervals contains more than one seasonal pattern, which are the intraday and intraweek seasonal cycles. The forecasts produced by the Holt-Winters Taylor (HWT) exponential smoothing outperformed the traditional Holt-Winters and modified Holt-Winters exponential smoothing methods.