IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/5559242.html
   My bibliography  Save this article

Optimal Fractional Order Based on Fuzzy Control Scheme for Wind Farm Voltage Control with Reactive Power Compensation

Author

Listed:
  • Kamal Elyaalaoui
  • Moussa Labbadi
  • Mohammed Ouassaid
  • Mohamed Cherkaoui

Abstract

Voltage stability margin is ensured through the reactive power resources. In order to generate the reactive power references and ensure the low-voltage ride-through (LVRT) control of a wind farm system based on squirrel cage induction generator, this paper proposed an optimal control approach based on fractional-order (FO) PI-fuzzy-PI (FOPI-fuzzy-FOPI) controller. The proposed control method ensures, also, the demand for active and reactive power predetermined by the transmission system operator (TSO) and satisfies the grid code recommendations. In order to achieve a faster tracking of state variables of the system, the FO operators are optimized using the particle swarm optimization algorithm (PSOA). Using FO operator and PSOA, the responses of the system can be improved. The proposed controller provides additional parameters for better tracking performance and faster convergence can be achieved. Numerical simulation results are presented to analyze the advantages of the proposed control approach to design a physically, realizable controller. The present results are compared with various control methods to show the superiority of the method proposed in this paper.

Suggested Citation

  • Kamal Elyaalaoui & Moussa Labbadi & Mohammed Ouassaid & Mohamed Cherkaoui, 2021. "Optimal Fractional Order Based on Fuzzy Control Scheme for Wind Farm Voltage Control with Reactive Power Compensation," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, March.
    • Handle: RePEc:hin:jnlmpe:5559242
    DOI: 10.1155/2021/5559242
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/5559242.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2021/5559242.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/5559242?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nathan Oaks Farrar & Mohd Hasan Ali & Dipankar Dasgupta, 2023. "Artificial Intelligence and Machine Learning in Grid Connected Wind Turbine Control Systems: A Comprehensive Review," Energies, MDPI, vol. 16(3), pages 1-25, February.

    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:hin:jnlmpe:5559242. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.