Forecasting electricity prices : a machine learning approach

Castelli, Mauro (author), Groznik, Aleš (author), Popovič, Aleš (author)

The electricity market is a complex, evolutionary, and dynamic environment. Forecasting electricity prices is an important issue for all electricity market participants. In this study, we shed light on how to improve electricity price forecasting accuracy through the use of a machine learning technique—namely, a novel genetic programming approach. Drawing on empirical data from the largest EU energy markets, we propose a forecasting model that considers variables related to weather conditions, oil prices, and CO2 coupons and predicts energy prices 24 h ahead. We show that the proposed model provides more accurate predictions of future electricity prices than existing prediction methods. Our important findings will assist the electricity market participants in forecasting future price movements.

• Language: English
• Keywords: energetics, price, informatics, energy sector, electricity prices, forecasting, machine learning, geometric semantic, based programming
• Work type: Article
• Typology: 1.01 - Original Scientific Article
• Organization: EF - School of Economics and Business
• Publication status: Published
• Publication version: Version of Record
• Year: 2020
• Number of pages: 16 str.
• Numbering: Vol. 13, iss. 5, art. 119
• PID: 20.500.12556/RUL-116491
• UDC: 659.2:004
• ISSN on article: 1999-4893
• DOI: 10.3390/a13050119
• COBISS.SI-ID: 14509571
• Publication date in RUL: 25.05.2020

CASTELLI, Mauro, GROZNIK, Aleš and POPOVIČ, Aleš, 2020, Forecasting electricity prices : a machine learning approach. Algorithms [online]. 2020. Vol. 13, no. 5,  119. [Accessed 11 April 2025]. DOI 10.3390/a13050119. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=116491

Record is a part of a journal

• Title: Algorithms
• Shortened title: Algorithms
• Publisher: MDPI
• ISSN: 1999-4893
• COBISS.SI-ID: 517501977

Licences

• License: CC BY 4.0, Creative Commons Attribution 4.0 International
• Link: http://creativecommons.org/licenses/by/4.0/
• Description: This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
• Licensing start date: 08.05.2020

Secondary language

• Language: Slovenian
• Keywords: energetika, cena, informatika

Projects

• Funder: ARRS - Slovenian Research Agency
• Project number: J5-9329
• Name: Poslovna analitika in poslovni modeli v oskrbovalnih verigah

• Funder: FCT - Fundação para a Ciência e a Tecnologia, I.P.
• Project number: DSAIPA/DS/0022/2018
• Acronym: GADgET