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Lookup NU author(s): Rina Haiges, Dr Yaodong WangORCiD, Professor Atanu Ghoshray, Professor Tony Roskilly
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2017 The Authors. Published by Elsevier Ltd. It is imperative for Malaysia to have a clear understanding of the future performance of its power sector with emphasis on the total installed capacity variable as this is integral to support the nation's capacity succession planning over an intermediate to long term period in order to sustain the economy. This paper aims to deploy the Auto Regressive Integrated Moving Average (ARIMA) approach to fit the 40 years forecast up to 2053 by assessing 40 years of past data from 1973 until 2013. The different models will be evaluated using the Schwarz Bayesian Criterion (SBC). Validation was performed by comparison of forecast and actual data based on a five-year holdback period. Accuracy measures applied were the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). In this assessment, ARIMA(0,2) demonstrated a better forecast in terms of accuracy during the holdback period. However, the Diebold-Mariano (DM) test didn't detect any differences between the ARIMA(1,0) and ARIMA(0,2) forecasts. Application of the forecast results was demonstrated as well.
Author(s): Haiges R, Wang YD, Ghoshray A, Roskilly AP
Editor(s): Jinyue Yan, Fengchun Sun, SK Chou, Umberto Desideri, Hailong Li, Pietro Campana and Rui Xiong
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 8th International Conference on Applied Energy (ICAE2016)
Year of Conference: 2017
Pages: 3471-3478
Print publication date: 01/05/2017
Online publication date: 01/06/2017
Acceptance date: 02/04/2016
Date deposited: 18/07/2017
ISSN: 1876-6102
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.egypro.2017.03.795
DOI: 10.1016/j.egypro.2017.03.795
Series Title: Energy Procedia
