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Moving holidays' effects on the Malaysian peak daily load

Malaysia’s yearly steady growth in electricity consumption as a result of fast development in various sectors of the Malaysian economy have increased the need to have a more robust, reliable and accurate load forecasting for short -, medium-, or long-term. A reliable method for short term load forec...

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Main Authors: Abd. Razak, Fadhilah, Hashim, Amir Hisham, Zainal Abidin, Izham, Shitan, Mahendran
Format: Conference or Workshop Item
Language:English
Published: IEEE 2010
Online Access:http://psasir.upm.edu.my/id/eprint/45747/1/Moving%20holidays%27%20effects%20on%20the%20Malaysian%20peak%20daily%20load.pdf
http://psasir.upm.edu.my/id/eprint/45747/
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spelling my.upm.eprints.457472020-08-07T02:59:33Z http://psasir.upm.edu.my/id/eprint/45747/ Moving holidays' effects on the Malaysian peak daily load Abd. Razak, Fadhilah Hashim, Amir Hisham Zainal Abidin, Izham Shitan, Mahendran Malaysia’s yearly steady growth in electricity consumption as a result of fast development in various sectors of the Malaysian economy have increased the need to have a more robust, reliable and accurate load forecasting for short -, medium-, or long-term. A reliable method for short term load forecasting is crucial to any decision maker in a power utility company. Many studies have been made to improve the forecasting accuracy using various methods. The forecasting errors for the holiday seasons are known to be higher than those for weekends. This paper aims to determine which model would be a better model to estimate the holiday effects and therefore give a better forecasting accuracy for the peak daily load in Malaysia. Some of the holiday effects in Malaysia are from Eid ul-Fitr, Christmas, Independence Day and Chinese New Year. The seasonal ARIMA (SARIMA) and Dynamic Regression (DR) or Transfer function modelling are considered. Furthermore, the final selection of the models depends on the Mean Absolute Percentage Error (MAPE) and others such as the sample autocorrelation function (ACF), the sample partial autocorrelation function (PACF) and a bias-corrected version of the Akaike’s information criterion (AICC) statistic. The Dynamic Regression (DR) model recorded 2.22% as the lowest MAPE value for the 2004 New Year’s Eve and 2.39% for the seven days ahead forecasting. And therefore, DR model is the most appropriate model to be considered for forecasting any public holidays in Malaysia. IEEE 2010 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/45747/1/Moving%20holidays%27%20effects%20on%20the%20Malaysian%20peak%20daily%20load.pdf Abd. Razak, Fadhilah and Hashim, Amir Hisham and Zainal Abidin, Izham and Shitan, Mahendran (2010) Moving holidays' effects on the Malaysian peak daily load. In: 2010 IEEE International Conference on Power and Energy (PECon 2010), 29 Nov.-1 Dec. 2010, Kuala Lumpur, Malaysia. (pp. 906-910). 10.1109/PECON.2010.5697708
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Malaysia’s yearly steady growth in electricity consumption as a result of fast development in various sectors of the Malaysian economy have increased the need to have a more robust, reliable and accurate load forecasting for short -, medium-, or long-term. A reliable method for short term load forecasting is crucial to any decision maker in a power utility company. Many studies have been made to improve the forecasting accuracy using various methods. The forecasting errors for the holiday seasons are known to be higher than those for weekends. This paper aims to determine which model would be a better model to estimate the holiday effects and therefore give a better forecasting accuracy for the peak daily load in Malaysia. Some of the holiday effects in Malaysia are from Eid ul-Fitr, Christmas, Independence Day and Chinese New Year. The seasonal ARIMA (SARIMA) and Dynamic Regression (DR) or Transfer function modelling are considered. Furthermore, the final selection of the models depends on the Mean Absolute Percentage Error (MAPE) and others such as the sample autocorrelation function (ACF), the sample partial autocorrelation function (PACF) and a bias-corrected version of the Akaike’s information criterion (AICC) statistic. The Dynamic Regression (DR) model recorded 2.22% as the lowest MAPE value for the 2004 New Year’s Eve and 2.39% for the seven days ahead forecasting. And therefore, DR model is the most appropriate model to be considered for forecasting any public holidays in Malaysia.
format Conference or Workshop Item
author Abd. Razak, Fadhilah
Hashim, Amir Hisham
Zainal Abidin, Izham
Shitan, Mahendran
spellingShingle Abd. Razak, Fadhilah
Hashim, Amir Hisham
Zainal Abidin, Izham
Shitan, Mahendran
Moving holidays' effects on the Malaysian peak daily load
author_facet Abd. Razak, Fadhilah
Hashim, Amir Hisham
Zainal Abidin, Izham
Shitan, Mahendran
author_sort Abd. Razak, Fadhilah
title Moving holidays' effects on the Malaysian peak daily load
title_short Moving holidays' effects on the Malaysian peak daily load
title_full Moving holidays' effects on the Malaysian peak daily load
title_fullStr Moving holidays' effects on the Malaysian peak daily load
title_full_unstemmed Moving holidays' effects on the Malaysian peak daily load
title_sort moving holidays' effects on the malaysian peak daily load
publisher IEEE
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/45747/1/Moving%20holidays%27%20effects%20on%20the%20Malaysian%20peak%20daily%20load.pdf
http://psasir.upm.edu.my/id/eprint/45747/
_version_ 1675328737377255424
score 13.211869

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