IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v8y2015i8p8908-8923d54575.html
   My bibliography  Save this article

Interval Type-II Fuzzy Rule-Based STATCOM for Voltage Regulation in the Power System

Author

Listed:
  • Ying-Yi Hong

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan)

  • Yu-Lun Hsieh

    (Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan)

Abstract

The static synchronous compensator (STATCOM) has recently received much attention owing to its ability to stabilize power systems and mitigate voltage variations. This paper investigates a novel interval type-II fuzzy rule-based PID ( proportional-integral-derivative ) controller for the STATCOM to mitigate bus voltage variations caused by large changes in load and the intermittent generation of photovoltaic (PV) arrays. The proposed interval type-II fuzzy rule base utilizes the output of the PID controller to tune the signal applied to the STATCOM. The rules involve upper and lower membership functions that ensure the stable responses of the controlled system. The proposed method is implemented using the NEPLAN software package and MATLAB/Simulink with co-simulation. A six-bus system is used to show the effectiveness of the proposed method. Comparative studies show that the proposed method is superior to traditional PID and type-I fuzzy rule-based methods.

Suggested Citation

  • Ying-Yi Hong & Yu-Lun Hsieh, 2015. "Interval Type-II Fuzzy Rule-Based STATCOM for Voltage Regulation in the Power System," Energies, MDPI, vol. 8(8), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:8:p:8908-8923:d:54575
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/8/8/8908/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/8/8/8908/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Ammar Hussein Mutlag & Azah Mohamed & Hussain Shareef, 2016. "A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board," Energies, MDPI, vol. 9(3), pages 1-32, February.
    2. Ping-Kui Wang & Yu-Jen Liu & Jun-Tinn Lin & Zen-Wei Wang & Hsu-Chih Cheng & Bo-Xuan Huang & Gary W. Chang, 2022. "Harris Hawks Optimization-Based Algorithm for STATCOM Voltage Regulation of Offshore Wind Farm Grid," Energies, MDPI, vol. 15(9), pages 1-24, April.
    3. Ying-Yi Hong, 2016. "Electric Power Systems Research," Energies, MDPI, vol. 9(10), pages 1-4, October.

    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:gam:jeners:v:8:y:2015:i:8:p:8908-8923:d:54575. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.