Application of autoregressive integrated moving average modelling for the forecasting of solar, wind, spot and options electricity prices: The australian national electricity market

Loading...
Thumbnail Image
File version

Version of Record (VoR)

Author(s)
Alsaedi, Y
Tularam, GA
Wong, V
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2019
Size
File type(s)
Location
Abstract

This study aims to develop autoregressive integrated moving average (ARIMA) models to predict the solar, wind, spot and options pricing over the next two years, with historical data being used in a univariate manner to understand market behaviour in terms of trends. The assessment is made in the context of the Australian National Electricity Market (ANEM). The ARIMA models predict the future values of the monthly solar, wind, spot and options prices for various Australian states using time-series data from January 2006 to March 2018. The results show increases from 30.46–40.42% for the spot electricity prices and from 14.80–15.13% for the options electricity prices in the ANEM with a two-year horizon. The results further show that wind prices are expected to increase by an average of 5.43%. However, the results also show that the average solar electricity prices will decrease by 67.7%.

Journal Title

International Journal of Energy Economics and Policy

Conference Title
Book Title
Edition
Volume

9

Issue

4

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement

© The Author(s) 2019. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Item Access Status
Note
Access the data
Related item(s)
Subject

Applied economics

Policy and administration

Persistent link to this record
Citation

Alsaedi, Y; Tularam, GA; Wong, V, Application of autoregressive integrated moving average modelling for the forecasting of solar, wind, spot and options electricity prices: The australian national electricity market, International Journal of Energy Economics and Policy, 2019, 9 (4), pp. 263-272

Collections