Forecasting electricity consumption using the second-order fuzzy time series
There is a great development of Universiti Tun Hussein Onn Malaysia (UTHM) infrastructure since its formation in 1993. The development will be accompanied by the increasing demand for electricity. Hence, there is a need to forecast UTHM electricity consumption accurately so that UTHM can plan for fu...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2020
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6209/1/Forecasting%20electricity%20consumption%20using%20the%20second-order%20fuzzy%20time%20series.pdf http://eprints.uthm.edu.my/6209/ https://doi.org/10.1088/1757-899X/932/1/012056 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1833418037490876416 |
|---|---|
| author | Tay, K. G. Sim, S. E. Tiong, W. K. Huong, Audrey |
| author_facet | Tay, K. G. Sim, S. E. Tiong, W. K. Huong, Audrey |
| author_sort | Tay, K. G. |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | There is a great development of Universiti Tun Hussein Onn Malaysia (UTHM) infrastructure since its formation in 1993. The development will be accompanied by the increasing demand for electricity. Hence, there is a need to forecast UTHM electricity consumption accurately so that UTHM can plan for future energy demand and utility saving decisions. Previous studies on UTHM electricity consumption prediction have been carried out using time series models, multiple linear regression and first-order fuzzy time series (FTS). The first-order FTS yield the best accuracy among these three methods. Previous forecasting problem showed higher order FTS can yield better accuracy. Therefore, in this study, the second-order FTS with trapezoidal membership function was implemented on the UTHM monthly electricity consumption from January 2009 to December 2018 to forecast January to December 2019 monthly electricity consumption. The procedure of the FTS and trapezoidal membership function was described together with January data. The second-order FTS forecast UTHM electricity consumption better than the first-order FTS. |
| format | Conference or Workshop Item |
| id | my.uthm.eprints-6209 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2020 |
| record_format | eprints |
| spelling | my.uthm.eprints-62092022-01-31T06:45:46Z http://eprints.uthm.edu.my/6209/ Forecasting electricity consumption using the second-order fuzzy time series Tay, K. G. Sim, S. E. Tiong, W. K. Huong, Audrey TK Electrical engineering. Electronics Nuclear engineering There is a great development of Universiti Tun Hussein Onn Malaysia (UTHM) infrastructure since its formation in 1993. The development will be accompanied by the increasing demand for electricity. Hence, there is a need to forecast UTHM electricity consumption accurately so that UTHM can plan for future energy demand and utility saving decisions. Previous studies on UTHM electricity consumption prediction have been carried out using time series models, multiple linear regression and first-order fuzzy time series (FTS). The first-order FTS yield the best accuracy among these three methods. Previous forecasting problem showed higher order FTS can yield better accuracy. Therefore, in this study, the second-order FTS with trapezoidal membership function was implemented on the UTHM monthly electricity consumption from January 2009 to December 2018 to forecast January to December 2019 monthly electricity consumption. The procedure of the FTS and trapezoidal membership function was described together with January data. The second-order FTS forecast UTHM electricity consumption better than the first-order FTS. 2020 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/6209/1/Forecasting%20electricity%20consumption%20using%20the%20second-order%20fuzzy%20time%20series.pdf Tay, K. G. and Sim, S. E. and Tiong, W. K. and Huong, Audrey (2020) Forecasting electricity consumption using the second-order fuzzy time series. In: 1st International Conference on Science, Engineering and Technology (ICSET) 2020, 27th February 2020, Pulau Pinang, Malaysia. https://doi.org/10.1088/1757-899X/932/1/012056 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Tay, K. G. Sim, S. E. Tiong, W. K. Huong, Audrey Forecasting electricity consumption using the second-order fuzzy time series |
| title | Forecasting electricity consumption using the second-order fuzzy time series |
| title_full | Forecasting electricity consumption using the second-order fuzzy time series |
| title_fullStr | Forecasting electricity consumption using the second-order fuzzy time series |
| title_full_unstemmed | Forecasting electricity consumption using the second-order fuzzy time series |
| title_short | Forecasting electricity consumption using the second-order fuzzy time series |
| title_sort | forecasting electricity consumption using the second-order fuzzy time series |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.uthm.edu.my/6209/1/Forecasting%20electricity%20consumption%20using%20the%20second-order%20fuzzy%20time%20series.pdf http://eprints.uthm.edu.my/6209/ https://doi.org/10.1088/1757-899X/932/1/012056 |
| url_provider | http://eprints.uthm.edu.my/ |