IDEAS home Printed from https://ideas.repec.org/a/igg/jsir00/v11y2020i4p24-60.html
   My bibliography  Save this article

Renewable Energy-Based Economic Load Dispatch Using Two-Step Biogeography-Based Optimization and Butterfly Optimization Algorithm

Author

Listed:
  • Subham Kundu

    (Kalyani Governmennt Engineering College, India)

  • Provas Kumar Roy

    (Kalyani Government Engineering College, India)

  • Barun Mandal

    (Kalyani Government Engineering College, India)

Abstract

This article introduces a unified approach to solve economic load dispatch (ELD) problem of an integrated power system that comprise of traditional thermal power units and renewable sources of energy such as wind energy (WE) and solar photovoltaic (PV) sources; employing a two-step optimization method consisting of Biogeography Based Optimization (BBO) and Butterfly Optimization Algorithm (BOA). BOA imitates the mating and food search process of butterflies for solving the problems associated with global optimization. Nonlinear characteristics of thermal generators is considered in the problem. Weibull distribution is used for determining the uncertainness in availability of wind power and Lognormal PDF is employed for calculating the availability of solar power. The efficacy, robustness and supremacy of the two-step BBO-BOA (hBBO-BOA) technique, compared to various other approaches in literature, are demonstrated by the simulation results. The outcome is quite inspiring, indicates that proposed hBBO-BOA is an efficient approach in order to solve different ELD problems.

Suggested Citation

  • Subham Kundu & Provas Kumar Roy & Barun Mandal, 2020. "Renewable Energy-Based Economic Load Dispatch Using Two-Step Biogeography-Based Optimization and Butterfly Optimization Algorithm," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 11(4), pages 24-60, October.
    • Handle: RePEc:igg:jsir00:v:11:y:2020:i:4:p:24-60
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSIR.2020100102
    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:11:y:2020:i:4:p:24-60. 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.