IDEAS home Printed from https://ideas.repec.org/a/igg/jeoe00/v5y2016i4p1-25.html
   My bibliography  Save this article

A Comparative Study of Improved Teaching Learning Based Optimization Technique on Economic Load Dispatch Problem with Generator Constraints

Author

Listed:
  • Sumit Banerjee

    (Electrical Engineering Department, Dr. B. C. Roy Engineering College Durgapur, Durgapur, India)

  • Chandan Chanda

    (Electrical Engineering Department, Indian Institute of Engineering Science and Technology Shibpur, Howrah, India)

  • Deblina Maity

    (Electrical Engineering Department, Netaji Subhash Engineering College, Kokata, India)

Abstract

This article presents a novel improved teaching learning based optimization (I-TLBO) technique to solve economic load dispatch (ELD) problem of the thermal plant without considering transmission losses. The proposed methodology can take care of ELD problems considering practical nonlinearities such as ramp rate limit, prohibited operating zone and valve point loading. The objective of economic load dispatch is to determine the optimal power generation of the units to meet the load demand, such that the overall cost of generation is minimized, while satisfying different operational constraints. I-TLBO is a recently developed evolutionary algorithm based on two basic concepts of education namely teaching phase and learning phase. The effectiveness of the proposed algorithm has been verified on test system with equality and inequality constraints. Compared with the other existing techniques demonstrates the superiority of the proposed algorithm.

Suggested Citation

  • Sumit Banerjee & Chandan Chanda & Deblina Maity, 2016. "A Comparative Study of Improved Teaching Learning Based Optimization Technique on Economic Load Dispatch Problem with Generator Constraints," International Journal of Energy Optimization and Engineering (IJEOE), IGI Global, vol. 5(4), pages 1-25, October.
    • Handle: RePEc:igg:jeoe00:v:5:y:2016:i:4:p:1-25
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJEOE.2016100101
    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:jeoe00:v:5:y:2016:i:4:p:1-25. 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.