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Recent Developments in the Modelling of Transformer Windings

Author

Listed:
  • Konstanty M. Gawrylczyk

    (Faculty of Electrical Engineering, West Pomeranian University of Technology, 70-310 Szczecin, Poland)

  • Szymon Banaszak

    (Faculty of Electrical Engineering, West Pomeranian University of Technology, 70-310 Szczecin, Poland)

Abstract

The paper provides a review of the modelling techniques used to simulate the frequency response of transformer windings. The aim of the research and development of modelling methods was to analyze the influence of deformations and faults in the windings on the changes in the frequency response. All described methods are given with examples of the modelling results performed by the authors of this paper and from literature sources. The research is prefaced with a thorough literature review. There are described models based on lumped parameters with input data coming from direct calculations based on the winding geometry and obtained from FEM modelling software and models considering the wave phenomena in the windings. The analysis was also performed for practical problems in winding modelling: the influence of windings other than the modelled one and the influence of parallel wires in a winding.

Suggested Citation

  • Konstanty M. Gawrylczyk & Szymon Banaszak, 2021. "Recent Developments in the Modelling of Transformer Windings," Energies, MDPI, vol. 14(10), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2798-:d:553871
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    References listed on IDEAS

    as
    1. Stefan Tenbohlen & Sebastian Coenen & Mohammad Djamali & Andreas Müller & Mohammad Hamed Samimi & Martin Siegel, 2016. "Diagnostic Measurements for Power Transformers," Energies, MDPI, vol. 9(5), pages 1-25, May.
    2. Szymon Banaszak & Konstanty Marek Gawrylczyk & Katarzyna Trela, 2020. "Frequency Response Modelling of Transformer Windings Connected in Parallel," Energies, MDPI, vol. 13(6), pages 1-13, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. 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.
    2. 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.

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