Forecasting day-ahead electricity prices of Singapore through ARIMA and wavelet-ARIMA

Authors

Kristine Joy E. Carpio, De La Salle University, Manila
Anne Marie L. Go, Bank of Singapore Limited
Camille Krisca M. Roncal, Institutional Shareholder Services, Inc.

College

College of Science

Department/Unit

Mathematics and Statistics Department

Document Type

Article

Source Title

DLSU Business and Economics Review

Volume

22

Issue

1

First Page

97

Last Page

118

Publication Date

7-1-2012

Abstract

The changes observed in the electricity markets over the past decade brought about developments in the field of electricity modeling. In this paper, traditional AutoRegressive Integrated Moving Average (ARIMA) models and Wavelet-ARIMA models arc applied to the Singapore electricity market, Asia's first liberalized electricity market. Forecasting will be done for each electricity price modelling technique and the adequacy of the models is tested through forecast accuracy. The comparison of forecast accuracy of the models is done across different data behaviors. Copyright © 2012 De La Salle University, Philippines.

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Recommended Citation

Carpio, K. E., Go, A. L., & Roncal, C. M. (2012). Forecasting day-ahead electricity prices of Singapore through ARIMA and wavelet-ARIMA. DLSU Business and Economics Review, 22 (1), 97-118. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/1851

Disciplines

Mathematics

Keywords

Box-Jenkins forecasting; Electric utilities—Rates--Singapore

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