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A Comprehensive Analysis of Windings Electrical and Mechanical Faults Using a High-Frequency Model

Author

Listed:
  • Mehran Tahir

    (Institute of Power Transmission and High Voltage Technology (IEH), Stuttgart University, Pfaffenwaldring 47, 70569 Stuttgart, Germany)

  • Stefan Tenbohlen

    (Institute of Power Transmission and High Voltage Technology (IEH), Stuttgart University, Pfaffenwaldring 47, 70569 Stuttgart, Germany)

Abstract

The measurement procedures for frequency response analysis (FRA) of power transformers are well documented in IEC and IEEE standards. However, the interpretation of FRA results is still far from reaching an accepted methodology and is limited to the analysis of the experts. The dilemma is that there are limited case studies available to understand the effect of different faults. Additionally, due to the destructive nature, it is not possible to apply the real mechanical deformations in the transformer windings to obtain the data. To solve these issues, in this contribution, the physical geometry of a three-phase transformer is simulated using 3D finite integration analysis to emulate the real transformer operation. The novelty of this model is that FRA traces are directly obtained from the 3D model of windings without estimating and solving lumped parameter circuit models. At first, the method is validated with a simple experimental setup. Afterwards, different mechanical and electrical faults are simulated, and their effects on FRA are discussed objectively. A key contribution of this paper is the winding assessment factor it introduces based on the standard deviation of difference (SDD) to detect and classify different electrical and mechanical faults. The results reveal that the proposed model provides the ability of precise and accurate fault simulation. By using SDD, different deviation patterns can be characterized for different faults, which makes fault classification possible. Thus, it provides a way forward towards the establishment of the standard algorithm for a reliable and automatic assessment of transformer FRA results.

Suggested Citation

  • Mehran Tahir & Stefan Tenbohlen, 2019. "A Comprehensive Analysis of Windings Electrical and Mechanical Faults Using a High-Frequency Model," Energies, MDPI, vol. 13(1), pages 1-25, December.
    • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:105-:d:301624
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    References listed on IDEAS

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    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.
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    Cited by:

    1. Omid Elahi & Reza Behkam & Gevork B. Gharehpetian & Fazel Mohammadi, 2022. "Diagnosing Disk-Space Variation in Distribution Power Transformer Windings Using Group Method of Data Handling Artificial Neural Networks," Energies, MDPI, vol. 15(23), pages 1-32, November.
    2. Mehran Tahir & Stefan Tenbohlen, 2021. "Transformer Winding Condition Assessment Using Feedforward Artificial Neural Network and Frequency Response Measurements," Energies, MDPI, vol. 14(11), pages 1-25, May.

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