IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2019i1p3-d299137.html
   My bibliography  Save this article

Quantitative Analysis of the Sensitivity of UHF Sensor Positions on a 420 kV Power Transformer Based on Electromagnetic Simulation

Author

Listed:
  • Chandra Prakash Beura

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

  • Michael Beltle

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

  • Stefan Tenbohlen

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

  • Martin Siegel

    (BSS Hochspannungstechnik GmbH, 71229 Leonberg, Germany)

Abstract

With an increasing interest in ultra-high frequency (UHF) partial discharge (PD) measurements for the continuous monitoring of power transformers, it is necessary to know where to place the UHF sensors on the tank wall. Placing a sensor in an area with many obstructions may lead to a decrease in sensitivity to the UHF signals. In this contribution, a previously validated simulation model of a three-phase 300 MVA, 420 kV power transformer is used to perform a sensitivity analysis to determine the most sensitive sensor positions on the tank wall when PD activity occurs inside the windings. A matrix of UHF sensors located on the transformer tank is used to perform the sensitivity analysis. Some of the windings are designed as layer windings, thus preventing the UHF signals from traveling through them and creating a realistic situation with very indirect propagation from source to sensor. Based on these findings, sensor configurations optimized for UHF signal sensitivity, which is also required for PD source localization, are recommended for localization purposes. Additionally, the propagation and attenuation of the UHF signals inside the windings and the tank are discussed in both oil and air.

Suggested Citation

  • Chandra Prakash Beura & Michael Beltle & Stefan Tenbohlen & Martin Siegel, 2019. "Quantitative Analysis of the Sensitivity of UHF Sensor Positions on a 420 kV Power Transformer Based on Electromagnetic Simulation," Energies, MDPI, vol. 13(1), pages 1-17, December.
  • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:3-:d:299137
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/1/3/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/1/3/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Martin Siegel & Sebastian Coenen & Michael Beltle & Stefan Tenbohlen & Marc Weber & Pascal Fehlmann & Stefan M. Hoek & Ulrich Kempf & Robert Schwarz & Thomas Linn & Jitka Fuhr, 2019. "Calibration Proposal for UHF Partial Discharge Measurements at Power Transformers," Energies, MDPI, vol. 12(16), pages 1-17, August.
    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. Łukasz Nagi & Michał Kozioł & Jarosław Zygarlicki, 2020. "Comparative Analysis of Optical Radiation Emitted by Electric Arc Generated at AC and DC Voltage," Energies, MDPI, vol. 13(19), pages 1-10, October.

    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. Vo-Nguyen Tuyet-Doan & Tien-Tung Nguyen & Minh-Tuan Nguyen & Jong-Ho Lee & Yong-Hwa Kim, 2020. "Self-Attention Network for Partial-Discharge Diagnosis in Gas-Insulated Switchgear," Energies, MDPI, vol. 13(8), pages 1-16, April.
    2. Shaorui Qin & Siyuan Zhou & Taiyun Zhu & Shenglong Zhu & Jianlin Li & Zheran Zheng & Shuo Qin & Cheng Pan & Ju Tang, 2021. "Sinusoidal Noise Removal in PD Measurement Based on Synchrosqueezing Transform and Singular Spectrum Analysis," Energies, MDPI, vol. 14(23), pages 1-22, November.
    3. Daria Wotzka & Wojciech Sikorski & Cyprian Szymczak, 2022. "Investigating the Capability of PD-Type Recognition Based on UHF Signals Recorded with Different Antennas Using Supervised Machine Learning," Energies, MDPI, vol. 15(9), pages 1-20, April.
    4. Stefan Tenbohlen & Chandra Prakash Beura & Wojciech Sikorski & Ricardo Albarracín Sánchez & Bruno Albuquerque de Castro & Michael Beltle & Pascal Fehlmann & Martin Judd & Falk Werner & Martin Siegel, 2023. "Frequency Range of UHF PD Measurements in Power Transformers," Energies, MDPI, vol. 16(3), pages 1-21, January.
    5. Michał Kozioł & Łukasz Nagi & Michał Kunicki & Ireneusz Urbaniec, 2019. "Radiation in the Optical and UHF Range Emitted by Partial Discharges," Energies, MDPI, vol. 12(22), pages 1-16, November.
    6. Chengjie Zhang & Yuan Li & Senhong Yang & Ranran Li, 2023. "Study on Development Characteristics of Partial Discharge in Oil-Pressboard Insulation under Constant DC Voltage," Energies, MDPI, vol. 16(10), pages 1-14, May.
    7. Michał Kunicki & Sebastian Borucki & Andrzej Cichoń & Jerzy Frymus, 2019. "Modeling of the Winding Hot-Spot Temperature in Power Transformers: Case Study of the Low-Loaded Fleet," Energies, MDPI, vol. 12(18), pages 1-17, September.
    8. Chandra Prakash Beura & Michael Beltle & Philipp Wenger & Stefan Tenbohlen, 2022. "Experimental Analysis of Ultra-High-Frequency Signal Propagation Paths in Power Transformers," Energies, MDPI, vol. 15(8), pages 1-15, April.
    9. Benhui Lai & Shichang Yang & Heng Zhang & Yiyi Zhang & Xianhao Fan & Jiefeng Liu, 2020. "Performance Assessment of Oil-Immersed Cellulose Insulator Materials Using Time–Domain Spectroscopy under Varying Temperature and Humidity Conditions," Energies, MDPI, vol. 13(17), pages 1-14, August.

    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:13:y:2019:i:1:p:3-:d:299137. 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.