IDEAS home Printed from https://ideas.repec.org/a/epw/ejece0/v3y2019i4id19096.html

A Novel Economic Dispatch in Power Grids Based on Enhanced Firework Algorithm

Author

Listed:
  • Iman Niazazari

    (University of Nevada, Reno,USA)

  • Oveis Asgari Gashteroodkhani

    (Department of Electrical and Biomedical Engineering, University of Nevada, Reno, USA)

  • Amir Niaz Azari

    (Department of Electrical Engineering, Azad University, Sari, Iran)

Abstract

This paper proposes a novel single objective optimization technique for economic dispatch (ED) in power grids. This new technique is developed based on firework algorithm (FWA) and is implemented in the IEEE 24 bus reliability test system. In this paper, the single-objective enhanced fireworks (EFWA) is developed to find the economic operating condition to minimize the generation cost. This method is a swarm intelligence algorithm that solves a single-objective optimization problem much faster than other well-known algorithms such as genetic algorithm (GA). The experimental results show that the proposed EFWA method is indeed capable of obtaining higher quality solutions efficiently in ED problems.

Suggested Citation

  • Iman Niazazari & Oveis Asgari Gashteroodkhani & Amir Niaz Azari, 2019. "A Novel Economic Dispatch in Power Grids Based on Enhanced Firework Algorithm," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 3(4), June.
  • Handle: RePEc:epw:ejece0:v:3:y:2019:i:4:id:19096
    DOI: 10.24018/ejece.2019.3.4.96
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejece/article/view/19096
    File Function: Abstract page
    Download Restriction: no

    File URL: https://eu-opensci.org/index.php/ejece/article/download/19096/11045
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.24018/ejece.2019.3.4.96?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
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:epw:ejece0:v:3:y:2019:i:4:id:19096. 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: support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejece .

    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.