IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i6p1325-d1354426.html
   My bibliography  Save this article

Current Compensation Method in a Distribution System Based on a Four-Leg Inverter under Unbalanced Load Conditions Using an Artificial Neural Network

Author

Listed:
  • Tae-Gyu Kim

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Chang-Gyun An

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Junsin Yi

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

  • Chung-Yuen Won

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea)

Abstract

This study proposes an unbalanced current compensation method based on a four-leg inverter using an artificial neural network (ANN) under unbalanced load conditions. Distribution systems exhibit rapid load variations, and conventional filter-based control methods suffer from the drawback of requiring an extended time period to reach a steady state. To address this problem, an ANN is applied to calculate the unbalanced current reference and enhance dynamic performance. Additionally, because of the periodic incorrect output inherent in the ANN, applying it to a proportional–integral controller would result in an error being directly reflected in the current reference. In the aforementioned problem, an ANN is applied to the dq0 coordinate system current controller to compensate for the periodic incorrect output in the current reference calculation. The proposed ANN-based unbalanced current compensation method is validated through PSIM simulations and experiments.

Suggested Citation

  • Tae-Gyu Kim & Chang-Gyun An & Junsin Yi & Chung-Yuen Won, 2024. "Current Compensation Method in a Distribution System Based on a Four-Leg Inverter under Unbalanced Load Conditions Using an Artificial Neural Network," Energies, MDPI, vol. 17(6), pages 1-29, March.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1325-:d:1354426
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/6/1325/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/6/1325/
    Download Restriction: no
    ---><---

    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:17:y:2024:i:6:p:1325-:d:1354426. 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.