IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v328y2025ics0360544225021723.html
   My bibliography  Save this article

Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster

Author

Listed:
  • Yang, Mao
  • Jiang, Renxian
  • Yu, Xinnan
  • Wang, Bo
  • Su, Xin
  • Ma, Chenglian

Abstract

With the continuous updating and iteration of artificial intelligence algorithms, prediction models emerge one after another, but the research and utilization of the predictability of wind power is still less. Therefore, this paper proposed a day-ahead power prediction method for Wind Farm Cluster (WFC) based on intrinsic predictable component extraction. Firstly, based on the difference of power distribution between wind farm and WFC, a method of Wind Power Curve (WPC) modeling for WFC is proposed, which provides the basis for establishing the Final Set of Wind Power Curve (FSWPC). Secondly, the Intrinsic Predictable Component (IPC) of wind power is extracted based on the FSWPC, and the Interference Component (IC) of wind power is separated to eliminate the influence of IC on IPC in the process of prediction. Thirdly, the historical similarity matching method with large threshold is used to predict the IC to make up for the numerical deficiency of the IPC. Finally, the proposed method was applied to a WFC in China to verify its effectiveness. Compared with the traditional prediction strategy, the NRMSE, NMAE and MAPE are reduced by 1.59 %, 1.15 % and 6.42 %, respectively.

Suggested Citation

  • Yang, Mao & Jiang, Renxian & Yu, Xinnan & Wang, Bo & Su, Xin & Ma, Chenglian, 2025. "Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster," Energy, Elsevier, vol. 328(C).
    • Handle: RePEc:eee:energy:v:328:y:2025:i:c:s0360544225021723
    DOI: 10.1016/j.energy.2025.136530
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225021723
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.136530?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:energy:v:328:y:2025:i:c:s0360544225021723. 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.journals.elsevier.com/energy .

    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.