IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v390y2025ics0306261925005434.html
   My bibliography  Save this article

An effective reserve capacity optimization method for power systems considering operational reliability with weather conditions

Author

Listed:
  • Dai, Wei
  • Shen, Haoran
  • Liu, Hui
  • Shi, Bochen

Abstract

A reasonable power system reserve is crucial for mitigating uncertain risks. However, determining an effective reserve that achieves both reliability and economics is challenging due to variable operating conditions and complex reliability calculations. This study proposes a reserve capacity optimization method that is embedded in operational reliability, considering multiple uncertainties. A set of operational reliability models for equipment is developed based on the operational status (current) and weather conditions (e.g., freezing rain, temperature, and wind speed). To reduce the computational complexity, a general analytical operational reliability method is proposed based on polynomial chaos expansion, considering the uncertainties of renewable energy, loads, and equipment failures. Using these analytical formulations, a two-stage reserve optimization model considering operational reliability is transformed into a single-stage optimization model, thereby enhancing the computational efficiency without compromising accuracy. Results demonstrate that the proposed method achieved reasonable reserve allocation with fast computation, balancing reliability and economics under variable operating conditions.

Suggested Citation

  • Dai, Wei & Shen, Haoran & Liu, Hui & Shi, Bochen, 2025. "An effective reserve capacity optimization method for power systems considering operational reliability with weather conditions," Applied Energy, Elsevier, vol. 390(C).
    • Handle: RePEc:eee:appene:v:390:y:2025:i:c:s0306261925005434
    DOI: 10.1016/j.apenergy.2025.125813
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261925005434
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2025.125813?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:appene:v:390:y:2025:i:c:s0306261925005434. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.