IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i8p3496-d1125546.html
   My bibliography  Save this article

Research on Online Detection Method of Transformer Winding Deformation Based on VFTO Characteristics

Author

Listed:
  • Xinghua Shi

    (Faculty of Science, Kunming University of Science and Technology, Kunming 650504, China)

  • Ran Wei

    (Faculty of Science, Kunming University of Science and Technology, Kunming 650504, China)

  • Wenbin Zhang

    (College of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650504, China)

Abstract

At present, most of the winding fault detections of transformers use offline methods, which require the entire line to be powered off or after the transformer has been shut down due to a serious fault, and they cannot detect the running status of the windings in real time and online. Since the transformer will be impacted by VFTO during operation, the VFTO is used as the excitation, and the basic principle of the frequency response method is used to propose an online detection method of transformer winding deformation based on VFTO characteristics. The finite element software is used to calculate the equivalent circuit parameters of normal and deformed windings, and the equivalent circuit model of the transformer windings before and after deformation is established. Due to the uncertainty of the VFTO waveform, combined with the frequency response method, the VFTO waveform is injected into the transformer winding health, and the frequency response curve is obtained from the deformed equivalent circuit, which is used to analyze the change of the resonance point in the case of radial deformation, axial deformation, and axial displacement of the winding. The simulation results show that with VFTO as the excitation, the obtained resonance point change can comprehensively reflect the deformation information of the winding. At the same time, the feasibility of the method is verified by experiments.

Suggested Citation

  • Xinghua Shi & Ran Wei & Wenbin Zhang, 2023. "Research on Online Detection Method of Transformer Winding Deformation Based on VFTO Characteristics," Energies, MDPI, vol. 16(8), pages 1-23, April.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3496-:d:1125546
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/8/3496/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/8/3496/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Song Wang & Ze Guo & Ting Zhu & Hanke Feng & Shuhong Wang, 2018. "A New Multi-Conductor Transmission Line Model of Transformer Winding for Frequency Response Analysis Considering the Frequency-Dependent Property of the Lamination Core," Energies, MDPI, vol. 11(4), pages 1-12, April.
    2. Konstanty M. Gawrylczyk & Szymon Banaszak, 2021. "Recent Developments in the Modelling of Transformer Windings," Energies, MDPI, vol. 14(10), pages 1-22, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Jiawei Wang & Yijing Xing & Xikui Ma & Zhiwei Zhao & Lihui Yang, 2023. "Numerical Investigations for Vibration and Deformation of Power Transformer Windings under Short-Circuit Condition," Energies, MDPI, vol. 16(14), pages 1-18, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Przemyslaw Goscinski & Zbigniew Nadolny & Andrzej Tomczewski & Ryszard Nawrowski & Tomasz Boczar, 2023. "The Influence of Heat Transfer Coefficient α of Insulating Liquids on Power Transformer Cooling Systems," Energies, MDPI, vol. 16(6), pages 1-15, March.
    2. Micah Phillip & Arvind Singh & Craig J. Ramlal, 2023. "Narrow Band Frequency Response Analysis of Power Transformers with Deep Learning," Energies, MDPI, vol. 16(17), pages 1-14, September.

    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:16:y:2023:i:8:p:3496-:d:1125546. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.