IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04288711.html
   My bibliography  Save this paper

Impact of renewable energy generation on power reserve energy demand

Author

Listed:
  • Laureen Deman

    (GAEL - Laboratoire d'Economie Appliquée de Grenoble - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, SuperGrid Institute SAS)

  • Quentin Boucher

    (SuperGrid Institute SAS)

Abstract

With increasing shares of renewable energy generation, the evolution of reserve needs may represent an important challenge for the power system. The evolution of reserve capacity needs in this context has been extensively studied in the literature (Hirth and Ziegenhagen, 2015). On the other hand, reserve energy needs have been less studied. This work focuses on analysing the relationship between reserve energy demand and load, wind, and solar generation. To this end, autoregressive models with exogenous variables are estimated on 2019 data of the French power system. We find a positive impact of renewable energy generation on downward reserve energy demand and a negative impact on upward reserve energy demand. These results can be interpreted through the relationship between the level of residual load and the probability to find a counterpart on the intraday market to balance forecast errors, thus allowing to reduce the imbalance of the system in real-time and thus the need for reserve energy.

Suggested Citation

  • Laureen Deman & Quentin Boucher, 2023. "Impact of renewable energy generation on power reserve energy demand," Post-Print hal-04288711, HAL.
    • Handle: RePEc:hal:journl:hal-04288711
    DOI: 10.1016/j.eneco.2023.107173
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Deng, Xu & Lv, Tao & Meng, Xiangyun & Li, Cong & Hou, Xiaoran & Xu, Jie & Wang, Yinhao & Liu, Feng, 2024. "Assessing the carbon emission reduction effect of flexibility option for integrating variable renewable energy," Energy Economics, Elsevier, vol. 132(C).

    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:hal:journl:hal-04288711. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.