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Double seasonal ARIMA model for forecasting load demand

This study investigates the use of a double seasonal ARIMA model for forecasting load demand. For the purpose of this study, a one-year half hourly Malaysia load demand from 1 September 2005 to 31 August 2006 measured in Megawatt (MW) is used. The mean absolute percentage error (MAPE) is used as the...

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Main Authors: Mohamed, Norizan, Ahmad, Maizah Hura, Ismail, Zuhaimy, Suhartono, Suhartono
Format: Article
Language:English
English
Published: Department of Mathematics, UTM 2010
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/36668/1/MaizahHuraAhmad2010_DoubleSeasonalARIMAModelforForecasting.pdf
http://eprints.utm.my/id/eprint/36668/2/201026211.pdf
http://eprints.utm.my/id/eprint/36668/
http://www.matematika.utm.my/index.php/matematika/article/view/565
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spelling my.utm.366682017-02-20T08:21:13Z http://eprints.utm.my/id/eprint/36668/ Double seasonal ARIMA model for forecasting load demand Mohamed, Norizan Ahmad, Maizah Hura Ismail, Zuhaimy Suhartono, Suhartono QA Mathematics This study investigates the use of a double seasonal ARIMA model for forecasting load demand. For the purpose of this study, a one-year half hourly Malaysia load demand from 1 September 2005 to 31 August 2006 measured in Megawatt (MW) is used. The mean absolute percentage error (MAPE) is used as the measure of forecasting accuracy. We use Statistical Analysis System, SAS package to analyze the data. Using the least squares method to estimate the coefficients in a double SARIMA model, followed by model validation and model selection criteria, we propose ARIMA(0; 1; 1)(0; 1; 1)48(0; 1; 1)336 with in-sample MAPE of 0.9906% as the best model for this study. Comparing the forecasting performances by using k-step ahead forecasts and one-step ahead forecasts, we found that the MAPE for the one-step ahead out-sample forecasts from any horizon ranging from one week lead time to one month lead time are all less than 1%. We thus propose that a double seasonal ARIMA model with one-step ahead forecast as the most appropriate model for forecasting the two-seasonal cycles Malaysia load demand time series. Department of Mathematics, UTM 2010-12 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/36668/1/MaizahHuraAhmad2010_DoubleSeasonalARIMAModelforForecasting.pdf text/html en http://eprints.utm.my/id/eprint/36668/2/201026211.pdf Mohamed, Norizan and Ahmad, Maizah Hura and Ismail, Zuhaimy and Suhartono, Suhartono (2010) Double seasonal ARIMA model for forecasting load demand. Matematika, 26 (2). pp. 217-231. ISSN 0127-9602 http://www.matematika.utm.my/index.php/matematika/article/view/565
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
English
topic QA Mathematics
spellingShingle QA Mathematics
Mohamed, Norizan
Ahmad, Maizah Hura
Ismail, Zuhaimy
Suhartono, Suhartono
Double seasonal ARIMA model for forecasting load demand
description This study investigates the use of a double seasonal ARIMA model for forecasting load demand. For the purpose of this study, a one-year half hourly Malaysia load demand from 1 September 2005 to 31 August 2006 measured in Megawatt (MW) is used. The mean absolute percentage error (MAPE) is used as the measure of forecasting accuracy. We use Statistical Analysis System, SAS package to analyze the data. Using the least squares method to estimate the coefficients in a double SARIMA model, followed by model validation and model selection criteria, we propose ARIMA(0; 1; 1)(0; 1; 1)48(0; 1; 1)336 with in-sample MAPE of 0.9906% as the best model for this study. Comparing the forecasting performances by using k-step ahead forecasts and one-step ahead forecasts, we found that the MAPE for the one-step ahead out-sample forecasts from any horizon ranging from one week lead time to one month lead time are all less than 1%. We thus propose that a double seasonal ARIMA model with one-step ahead forecast as the most appropriate model for forecasting the two-seasonal cycles Malaysia load demand time series.
format Article
author Mohamed, Norizan
Ahmad, Maizah Hura
Ismail, Zuhaimy
Suhartono, Suhartono
author_facet Mohamed, Norizan
Ahmad, Maizah Hura
Ismail, Zuhaimy
Suhartono, Suhartono
author_sort Mohamed, Norizan
title Double seasonal ARIMA model for forecasting load demand
title_short Double seasonal ARIMA model for forecasting load demand
title_full Double seasonal ARIMA model for forecasting load demand
title_fullStr Double seasonal ARIMA model for forecasting load demand
title_full_unstemmed Double seasonal ARIMA model for forecasting load demand
title_sort double seasonal arima model for forecasting load demand
publisher Department of Mathematics, UTM
publishDate 2010
url http://eprints.utm.my/id/eprint/36668/1/MaizahHuraAhmad2010_DoubleSeasonalARIMAModelforForecasting.pdf
http://eprints.utm.my/id/eprint/36668/2/201026211.pdf
http://eprints.utm.my/id/eprint/36668/
http://www.matematika.utm.my/index.php/matematika/article/view/565
_version_ 1643649997013516288
score 13.211869

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