IDEAS home Printed from https://ideas.repec.org/a/igg/jaec00/v1y2010i4p71-91.html
   My bibliography  Save this article

A Comparative Study of Metaheuristic Methods for Transmission Network Expansion Planning

Author

Listed:
  • Ashu R. Verma

    (TERI University, India)

  • P. K. Bijwe

    (IIT, India)

  • B. Panigrahi

    (IIT, India)

Abstract

Transmission network expansion planning is a very complex and computationally demanding problem due to the discrete nature of the optimization variables. This complexity has increased even more in a restructured deregulated environment. In this regard, there is a need for development of more rigorous optimization techniques. This paper presents a comparative analysis of three metaheuristic algorithms known as Bacteria foraging (BF), Genetic algorithm (GA), and Particle swarm optimization (PSO) for transmission network expansion planning with and without security constraints. The DC power flow based model is used for analysis and results for IEEE 24 bus system are obtained with the above three metaheuristic drawing a comparison of their performance characteristic.

Suggested Citation

  • Ashu R. Verma & P. K. Bijwe & B. Panigrahi, 2010. "A Comparative Study of Metaheuristic Methods for Transmission Network Expansion Planning," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 1(4), pages 71-91, October.
  • Handle: RePEc:igg:jaec00:v:1:y:2010:i:4:p:71-91
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaec.2010100104
    Download Restriction: no
    ---><---

    More about this item

    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:igg:jaec00:v:1:y:2010:i:4:p:71-91. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.