Malaysian day-type load forecasting
Time series analysis has been applied intensively and sophisticatedly to model and forecast many problems in the biological, physical and environmental phenomena of interest. This fact accounts for the basic engineering problem in forecasting the daily peak system load to use time series analysis. A...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2009
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| Online Access: | http://psasir.upm.edu.my/id/eprint/69586/ http://psasir.upm.edu.my/id/eprint/69586/1/Malaysian%20day-type%20load%20forecasting.pdf |
| _version_ | 1848856450113208320 |
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| author | Abd. Razak, Fadhilah S., Suriawati Hashim, Amir Hisham Zainal Abidin, Izham Shitan, Mahendran |
| author_facet | Abd. Razak, Fadhilah S., Suriawati Hashim, Amir Hisham Zainal Abidin, Izham Shitan, Mahendran |
| author_sort | Abd. Razak, Fadhilah |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Time series analysis has been applied intensively and sophisticatedly to model and forecast many problems in the biological, physical and environmental phenomena of interest. This fact accounts for the basic engineering problem in forecasting the daily peak system load to use time series analysis. ARMA and REgARMA models are among the times series models considered. ANFIS, a hybrid model from neural network is also discussed as for comparison purposes. The main interest of the forecasts consists of three days up to five days ahead predictions for daily data. The pure autoregressive model with an order 2, or AR (2) with a MAPE value of 1.27% is found to be an appropriate model for forecasting the Malaysian peak daily load for the 3 days ahead prediction. ANFIS model gives a better MAPE value when weekends' data were excluded. Regression models with ARMA errors are found to be good models for forecasting different day types. The selection of these models is depended on the smallest value of AIC statistic and the forecasting accuracy criteria. |
| first_indexed | 2025-11-15T11:41:51Z |
| format | Conference or Workshop Item |
| id | upm-69586 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:41:51Z |
| publishDate | 2009 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-695862019-07-04T05:01:47Z http://psasir.upm.edu.my/id/eprint/69586/ Malaysian day-type load forecasting Abd. Razak, Fadhilah S., Suriawati Hashim, Amir Hisham Zainal Abidin, Izham Shitan, Mahendran Time series analysis has been applied intensively and sophisticatedly to model and forecast many problems in the biological, physical and environmental phenomena of interest. This fact accounts for the basic engineering problem in forecasting the daily peak system load to use time series analysis. ARMA and REgARMA models are among the times series models considered. ANFIS, a hybrid model from neural network is also discussed as for comparison purposes. The main interest of the forecasts consists of three days up to five days ahead predictions for daily data. The pure autoregressive model with an order 2, or AR (2) with a MAPE value of 1.27% is found to be an appropriate model for forecasting the Malaysian peak daily load for the 3 days ahead prediction. ANFIS model gives a better MAPE value when weekends' data were excluded. Regression models with ARMA errors are found to be good models for forecasting different day types. The selection of these models is depended on the smallest value of AIC statistic and the forecasting accuracy criteria. IEEE 2009 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/69586/1/Malaysian%20day-type%20load%20forecasting.pdf Abd. Razak, Fadhilah and S., Suriawati and Hashim, Amir Hisham and Zainal Abidin, Izham and Shitan, Mahendran (2009) Malaysian day-type load forecasting. In: 3rd International Conference on Energy and Environment (ICEE 2009), 7-8 Dec. 2009, Malacca, Malaysia. (pp. 408-411). 10.1109/ICEENVIRON.2009.5398613 |
| spellingShingle | Abd. Razak, Fadhilah S., Suriawati Hashim, Amir Hisham Zainal Abidin, Izham Shitan, Mahendran Malaysian day-type load forecasting |
| title | Malaysian day-type load forecasting |
| title_full | Malaysian day-type load forecasting |
| title_fullStr | Malaysian day-type load forecasting |
| title_full_unstemmed | Malaysian day-type load forecasting |
| title_short | Malaysian day-type load forecasting |
| title_sort | malaysian day-type load forecasting |
| url | http://psasir.upm.edu.my/id/eprint/69586/ http://psasir.upm.edu.my/id/eprint/69586/ http://psasir.upm.edu.my/id/eprint/69586/1/Malaysian%20day-type%20load%20forecasting.pdf |