Cover Image

Improving short term load forecasting using double seasol arima model

Forecasting load demand with high accuracy is required to avoid energy wasting and prevent system failure. The aim of this paper is to develop a forecasting model based on double SARIMA for improving the accuracy of short term load prediction in Malaysia and compare the results with single SARIMA mo...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohamed, Norizan, Ahmad, Maizah Hura, Suhartono, Suhartono, Ismail, Zuhaimy
Format: Article
Published: International Digital Organization for Scientific Information (I D O S I) 2011
Subjects:
CB History of civilization
Online Access:http://eprints.utm.my/id/eprint/44977/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.44977
record_format eprints
spelling my.utm.449772017-01-31T06:08:47Z http://eprints.utm.my/id/eprint/44977/ Improving short term load forecasting using double seasol arima model Mohamed, Norizan Ahmad, Maizah Hura Suhartono, Suhartono Ismail, Zuhaimy CB History of civilization Forecasting load demand with high accuracy is required to avoid energy wasting and prevent system failure. The aim of this paper is to develop a forecasting model based on double SARIMA for improving the accuracy of short term load prediction in Malaysia and compare the results with single SARIMA model. A half hourly load demand of Malaysia for 4 months, from September 01, 2005 to December 31, 2005 is used in this study with the mean absolute percentage error (MAPE) as one of the accuracy measures. The results of the identification step show that the load data have two seasonal periods, i.e. daily and weekly seasonality with length 48 and 336 respectively. The estimation and diagnostic check steps show that the best order of double SARIMA for half hourly load demand of Malaysia is ARIMA([2,3,4,8,11,16,18,19,20,21,28,29,30,32,40,41,45,46,47],1,1)(0,1,1)48(0,1,1)336 with in-sample and out-sample MAPE values of 0.96840 and 4.49251 respectively. The in-sample and out-sample MAPE of a single SARIMA model are 1.07872 and 10.45530 respectively. Thus, the current study shows that the double SARIMA model performs better than single SARIMA model since the MAPE of in-sample and out-sample are reduced by 10.22676% and 57.03126% respectively. International Digital Organization for Scientific Information (I D O S I) 2011 Article PeerReviewed Mohamed, Norizan and Ahmad, Maizah Hura and Suhartono, Suhartono and Ismail, Zuhaimy (2011) Improving short term load forecasting using double seasol arima model. World Applied Sciences Journal, 15 (2). pp. 223-231. ISSN 1818-4952
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/
topic CB History of civilization
spellingShingle CB History of civilization
Mohamed, Norizan
Ahmad, Maizah Hura
Suhartono, Suhartono
Ismail, Zuhaimy
Improving short term load forecasting using double seasol arima model
description Forecasting load demand with high accuracy is required to avoid energy wasting and prevent system failure. The aim of this paper is to develop a forecasting model based on double SARIMA for improving the accuracy of short term load prediction in Malaysia and compare the results with single SARIMA model. A half hourly load demand of Malaysia for 4 months, from September 01, 2005 to December 31, 2005 is used in this study with the mean absolute percentage error (MAPE) as one of the accuracy measures. The results of the identification step show that the load data have two seasonal periods, i.e. daily and weekly seasonality with length 48 and 336 respectively. The estimation and diagnostic check steps show that the best order of double SARIMA for half hourly load demand of Malaysia is ARIMA([2,3,4,8,11,16,18,19,20,21,28,29,30,32,40,41,45,46,47],1,1)(0,1,1)48(0,1,1)336 with in-sample and out-sample MAPE values of 0.96840 and 4.49251 respectively. The in-sample and out-sample MAPE of a single SARIMA model are 1.07872 and 10.45530 respectively. Thus, the current study shows that the double SARIMA model performs better than single SARIMA model since the MAPE of in-sample and out-sample are reduced by 10.22676% and 57.03126% respectively.
format Article
author Mohamed, Norizan
Ahmad, Maizah Hura
Suhartono, Suhartono
Ismail, Zuhaimy
author_facet Mohamed, Norizan
Ahmad, Maizah Hura
Suhartono, Suhartono
Ismail, Zuhaimy
author_sort Mohamed, Norizan
title Improving short term load forecasting using double seasol arima model
title_short Improving short term load forecasting using double seasol arima model
title_full Improving short term load forecasting using double seasol arima model
title_fullStr Improving short term load forecasting using double seasol arima model
title_full_unstemmed Improving short term load forecasting using double seasol arima model
title_sort improving short term load forecasting using double seasol arima model
publisher International Digital Organization for Scientific Information (I D O S I)
publishDate 2011
url http://eprints.utm.my/id/eprint/44977/
_version_ 1643651604317995008
score 13.211869

Similar Items