IDEAS home Printed from https://ideas.repec.org/a/igg/jsir00/v13y2022i1p1-15.html
   My bibliography  Save this article

Sooty Tern Optimization Algorithm for Solving the Multi-Objective Dynamic Economic Emission Dispatch Problem

Author

Listed:
  • Jatin Soni

    (Institute of Technology, Nirma University, India)

  • Kuntal Bhattacharjee

    (Institute of Technology, Nirma University, India)

Abstract

The sooty tern optimization algorithm (STOA) has been used in this study to solve and optimize the dynamic economic emission dispatch (DEED) problem. The main aim of the DEED model is to minimize total fuel cost and emission of pollutant gases from thermal generators for 24 hours. The various operating constraints like valve point loading effect, ramp rate limit, transmission losses, operating conditions, and power balance constraints have been considered in this study to get a closer practical system. The swarm intelligence-based STOA method has been inspired by the migration and attacking behaviors of sea bird sooty tern. The exploration and exploitation approach of the proposed algorithm help to get an optimum solution in less convergence time. The algorithm has been tested in 5 and 10 thermal generating units to verify the algorithm's performance. The results obtained by the proposed algorithm have been compared with results obtained by other recently developed algorithms.

Suggested Citation

  • Jatin Soni & Kuntal Bhattacharjee, 2022. "Sooty Tern Optimization Algorithm for Solving the Multi-Objective Dynamic Economic Emission Dispatch Problem," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 13(1), pages 1-15, January.
  • Handle: RePEc:igg:jsir00:v:13:y:2022:i:1:p:1-15
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSIR.308292
    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:jsir00:v:13:y:2022:i:1:p:1-15. 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.