IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v353y2024ipbs0306261923015362.html
   My bibliography  Save this article

Small-signal stability enhancement of islanded microgrids via domain-enriched optimization

Author

Listed:
  • Kweon, Junho
  • Jing, Hang
  • Li, Yan
  • Monga, Vishal

Abstract

A domain-enriched optimization algorithm is developed to enhance the dynamic resilience of islanded microgrids, with a specific emphasis on improving small-signal stability. A novel eigenvalue-oriented objective function and accompanying constraints are designed to optimize the controller parameters for the power-electronic interfaces of distributed energy resources (DERs), which are critically important to the system’s dynamic resilience. To solve the resulting non-smooth and non-convex optimization problem, we introduce an auxiliary loss term based on microgrid domain knowledge, which takes the form of a multivariate polynomial in the optimization variables. We refer to our proposed method as Domain-Enriched Navigation (DEN), which combines the gradient of this domain-enriched loss term as a navigation strategy with an evolutionary algorithm. By incorporating the navigated update, we successfully address initialization sensitivity and slow convergence commonly observed in ordinary evolutionary algorithms. Numerical tests on typical islanded microgrids validate the effectiveness of our approach in enhancing the small-signal stability. Our results demonstrate a notable improvement of over 1 dB in the objective function, along with much faster computation than state-of-the-art alternatives.

Suggested Citation

  • Kweon, Junho & Jing, Hang & Li, Yan & Monga, Vishal, 2024. "Small-signal stability enhancement of islanded microgrids via domain-enriched optimization," Applied Energy, Elsevier, vol. 353(PB).
  • Handle: RePEc:eee:appene:v:353:y:2024:i:pb:s0306261923015362
    DOI: 10.1016/j.apenergy.2023.122172
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923015362
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.122172?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.

    Citations

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


    Cited by:

    1. Zhong Guan & Hui Wang & Zhi Li & Xiaohu Luo & Xi Yang & Jugang Fang & Qiang Zhao, 2024. "Multi-Objective Optimal Scheduling of Microgrids Based on Improved Particle Swarm Algorithm," Energies, MDPI, vol. 17(7), pages 1-20, April.

    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:353:y:2024:i:pb:s0306261923015362. 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.