Journals Information
Universal Journal of Electrical and Electronic Engineering Vol. 6(5B), pp. 26 - 36
DOI: 10.13189/ujeee.2019.061605
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Electricity Consumption Forecasting Using Nonlinear Autoregressive with External (Exogeneous) Input Neural Network
K. G. Tay 1,*, Hassan Muwafaq 1, Shuhaida Binti Ismail 2, Pauline Ong 3
1 Faculty of Electrical and Electronics Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia
2 Faculty of Applied Science and Technology, Universiti Tun Hussein Onn Malaysia, Malaysia
3 Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Malaysia
ABSTRACT
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%.
KEYWORDS
ANN, NARX, Electricity Consumption, Forecasting
Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] K. G. Tay , Hassan Muwafaq , Shuhaida Binti Ismail , Pauline Ong , "Electricity Consumption Forecasting Using Nonlinear Autoregressive with External (Exogeneous) Input Neural Network," Universal Journal of Electrical and Electronic Engineering, Vol. 6, No. 5B, pp. 26 - 36, 2019. DOI: 10.13189/ujeee.2019.061605.
(b). APA Format:
K. G. Tay , Hassan Muwafaq , Shuhaida Binti Ismail , Pauline Ong (2019). Electricity Consumption Forecasting Using Nonlinear Autoregressive with External (Exogeneous) Input Neural Network. Universal Journal of Electrical and Electronic Engineering, 6(5B), 26 - 36. DOI: 10.13189/ujeee.2019.061605.