Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network
Forecasting is prediction of future values based on historical data. Electricity consumption forecasting is crucial for utility company to plan for future power system generation. Even though there are previous works of electricity consumption forecasting using Artificial Neural Network (ANN), but m...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
HRPub
2019
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/642/ http://eprints.uthm.edu.my/642/1/DNJ9639_d037c088bf732c91c2b4c801eb6d1052.pdf |
| _version_ | 1848887252411744256 |
|---|---|
| author | K. G., Tay Muwafaq, Hassan Ismail, Shuhaida Ong, Pauline |
| author_facet | K. G., Tay Muwafaq, Hassan Ismail, Shuhaida Ong, Pauline |
| author_sort | K. G., Tay |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Forecasting is prediction of future values based on historical data. Electricity consumption forecasting is crucial for utility company to plan for future power system generation. Even though there are previous works of electricity consumption forecasting using Artificial Neural Network (ANN), but most of their data is multivariate data. In this study, we have only univariate data of electricity consumption from January 2009 to December 2018 and wish to do a prediction for a year ahead. On top of that, our data consist of autoregressive component, hence Nonlinear Autoregressive with External (Exogeneous) Input (NARX) Neural Network Time Series from Matlab R2018b was used. It gives the mean absolute percentage error (MAPE) between actual and predicted electricity consumption of 1.38%. |
| first_indexed | 2025-11-15T19:51:26Z |
| format | Article |
| id | uthm-642 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:51:26Z |
| publishDate | 2019 |
| publisher | HRPub |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-6422021-08-11T08:20:55Z http://eprints.uthm.edu.my/642/ Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network K. G., Tay Muwafaq, Hassan Ismail, Shuhaida Ong, Pauline TK3001-3521 Distribution or transmission of electric power Forecasting is prediction of future values based on historical data. Electricity consumption forecasting is crucial for utility company to plan for future power system generation. Even though there are previous works of electricity consumption forecasting using Artificial Neural Network (ANN), but most of their data is multivariate data. In this study, we have only univariate data of electricity consumption from January 2009 to December 2018 and wish to do a prediction for a year ahead. On top of that, our data consist of autoregressive component, hence Nonlinear Autoregressive with External (Exogeneous) Input (NARX) Neural Network Time Series from Matlab R2018b was used. It gives the mean absolute percentage error (MAPE) between actual and predicted electricity consumption of 1.38%. HRPub 2019 Article PeerReviewed text en http://eprints.uthm.edu.my/642/1/DNJ9639_d037c088bf732c91c2b4c801eb6d1052.pdf K. G., Tay and Muwafaq, Hassan and Ismail, Shuhaida and Ong, Pauline (2019) Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network. Universal Journal of Electrical and Electronic Engineering, 6 (5B). pp. 26-36. https://doi.org/10.13189/ujeee.2019.061605 |
| spellingShingle | TK3001-3521 Distribution or transmission of electric power K. G., Tay Muwafaq, Hassan Ismail, Shuhaida Ong, Pauline Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network |
| title | Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network |
| title_full | Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network |
| title_fullStr | Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network |
| title_full_unstemmed | Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network |
| title_short | Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network |
| title_sort | electricity consumption forecasting using nonlinear autoregressive with external (exogeneous) input neural network |
| topic | TK3001-3521 Distribution or transmission of electric power |
| url | http://eprints.uthm.edu.my/642/ http://eprints.uthm.edu.my/642/ http://eprints.uthm.edu.my/642/1/DNJ9639_d037c088bf732c91c2b4c801eb6d1052.pdf |