Forecasting electricity price in Colombia: A comparison between Neural Network, ARMA process and Hybrid Models

Jorge Barrientos Marin (), Elkin Tabares Orozco and Esteban Velilla
Additional contact information
Elkin Tabares Orozco: Department of Economics, Faculty of Economic Science, University of Antioquia, Medell n, Colombia,
Esteban Velilla: Department of Electrical Engineering, Faculty of Engineering, University of Antioquia, Medell n, Colombia

International Journal of Energy Economics and Policy, 2018, vol. 8, issue 3, 97-106

Abstract: This study aims to predict electricity prices in the Colombian electricity market. To achieve this goal, conventional time series econometrics analysis and one alternative technique based on artificial intelligence algorithms have been implemented. We use autoregressive-moving-average models (ARMAX) and non-linear autoregressive neural networks (NARX). After estimating a hybrid model that combines ARMAX and ARNX models, including exogenous inputs, we forecasted an electricity price time series in a horizon of 12 months ahead (May 2017). Results show that NARX model's performance is not significantly better than ARMAX's. After applying a Diebold-Mariano test for forecasting accuracy, the null hypothesis is not rejected. This suggests no significant difference in predictive accuracy between the competing methodologies.

Keywords: Stochastic Process; Autoregressive-moving-average; NARX; Random Walk; Predictive Accuracy; Electricity Spot Price (search for similar items in EconPapers)
JEL-codes: C01 C12 C22 C45 C53 L11 L94 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.econjournals.com/index.php/ijeep/article/download/6181/3684 (application/pdf)
https://www.econjournals.com/index.php/ijeep/article/view/6181/3684 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2018-03-15

Access Statistics for this article

International Journal of Energy Economics and Policy is currently edited by Ilhan Ozturk

More articles in International Journal of Energy Economics and Policy from Econjournals
Bibliographic data for series maintained by Ilhan Ozturk ().