IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v342y2023ics0306261923005172.html
   My bibliography  Save this article

A non-simulation-based linear model for analytical reliability evaluation of radial distribution systems considering renewable DGs

Author

Listed:
  • Alanazi, Mohana
  • Alanazi, Abdulaziz
  • Akbari, Mohammad Amin
  • Deriche, Mohamed
  • Memon, Zulfiqar Ali

Abstract

One of the most critical goals in the operation and planning of distribution networks is the creation of networks with sufficient reliability. Existing models are often simulation-based or try to introduce topology-independent algebraic reliability measures with simplifications or extensive computations. This paper presents new and efficient topology-variable-based linear expressions that can evaluate the reliability indices of practical radial distribution networks. Furthermore, the model is extended to consider the inclusion of renewable distributed generation (DG) units to restore part of restorable loads in the islanded mode of operation. Also, the stochastic nature of renewable generation, as well as load demand, is considered. Therefore, the proposed model can be readily used in various optimization models to operate and plan distribution networks with reliability concerns. The application of the proposed method to several small- to large-scale test cases ranging from standard 37-node up to practical 1080-node benchmarks shows the proposed model's accuracy and computational effectiveness compared to the state-of-the-art conventional simulation-based topology-variable-based approaches. The impact of the system's islanded operation on the reliability indices is also evaluated on the modified DG-enhanced 37-node test system.

Suggested Citation

  • Alanazi, Mohana & Alanazi, Abdulaziz & Akbari, Mohammad Amin & Deriche, Mohamed & Memon, Zulfiqar Ali, 2023. "A non-simulation-based linear model for analytical reliability evaluation of radial distribution systems considering renewable DGs," Applied Energy, Elsevier, vol. 342(C).
    • Handle: RePEc:eee:appene:v:342:y:2023:i:c:s0306261923005172
    DOI: 10.1016/j.apenergy.2023.121153
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923005172
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.121153?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.

    References listed on IDEAS

    as
    1. Jooshaki, Mohammad & Lehtonen, Matti & Fotuhi-Firuzabad, Mahmud & Muñoz-Delgado, Gregorio & Contreras, Javier & Arroyo, José M., 2022. "On the explicit formulation of reliability assessment of distribution systems with unknown network topology: Incorporation of DG, switching interruptions, and customer-interruption quantification," Applied Energy, Elsevier, vol. 324(C).
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Abdulaziz Alanazi & Tarek I. Alanazi, 2023. "Multi-Objective Framework for Optimal Placement of Distributed Generations and Switches in Reconfigurable Distribution Networks: An Improved Particle Swarm Optimization Approach," Sustainability, MDPI, vol. 15(11), pages 1-25, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:342:y:2023:i:c:s0306261923005172. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.