ARAR algorithm in forecasting electricity load demand in Malaysia

Miswan, Nor Hamizah and Hussin, Nor Hafizah and Mohd Said, Rahaini and Hamzah, Khairum and Ahmad, Emy Zairah (2016) ARAR algorithm in forecasting electricity load demand in Malaysia. Global Journal Of Pure And Applied Mathematics, 12 (1). pp. 361-367. ISSN 0973-1768

Text 19_43000- GJPAM 97 ok 361-367 author self1.pdf Download (341kB)

Abstract

Electricity load demand has grown more than four-fold over the last 20 years period. The purpose of the current study is to evaluate the performance of ARAR model in forecasting electricity load demand in Malaysia. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) will be used as a benchmark model since the model has been proven in many forecasting context. Using Root Mean Square Error (RMSE) as the forecasting performance measure, the study concludes that ARAR is more appropriate model.

Item Type:	Article
Uncontrolled Keywords:	Load forecasting, ARAR, ARIMA
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Engineering Technology
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	16 Aug 2016 02:58
Last Modified:	18 Jul 2023 12:08
URI:	http://eprints.utem.edu.my/id/eprint/16996
Statistic Details:	View Download Statistic

Actions (login required)

View Item