IDEAS home Printed from https://ideas.repec.org/a/eee/jocoma/v37y2025ics2405851324000680.html
   My bibliography  Save this article

Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market

Author

Listed:
  • Chȩć, Katarzyna
  • Uniejewski, Bartosz
  • Weron, Rafał

Abstract

Recent studies provide evidence that decomposing the electricity price into the long-term seasonal component (LTSC) and the remaining part, predicting both separately, and then combining their forecasts can bring significant accuracy gains in day-ahead electricity price forecasting. However, not much attention has been paid to predicting the LTSC, and the last 24 hourly values of the estimated pattern are typically copied for the target day. To address this gap, we introduce a novel approach which extracts the trend-seasonal pattern from a price series extrapolated using price forecasts for the next 24 h. We assess it using two 5-year long test periods from the German and Spanish power markets, covering the Covid-19 pandemic, the 2021/2022 energy crisis, and the war in Ukraine. Considering parsimonious autoregressive and LASSO-estimated models, we find that improvements in predictive accuracy range from 3% to 15% in terms of the root mean squared error and exceed 1% in terms of profits from a realistic trading strategy involving day-ahead bidding and battery storage.

Suggested Citation

  • Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
  • Handle: RePEc:eee:jocoma:v:37:y:2025:i:c:s2405851324000680
    DOI: 10.1016/j.jcomm.2024.100449
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S2405851324000680
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcomm.2024.100449?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jocoma:v:37:y:2025:i:c:s2405851324000680. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcomm .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.