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Effectiveness Analysis and Temperature Effect Mechanism on Chemical and Electrical-Based Transformer Insulation Diagnostic Parameters Obtained from PDC Data

Author

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  • Hanbo Zheng

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, Guangxi, China
    State Grid Henan Electric Power Research Institute, Zhengzhou 450052, Henan, China
    These authors contributed equally to this work.)

  • Jiefeng Liu

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, Guangxi, China
    Shijiazhuang Power Supply Branch of State Grid Electric Power Company, Shijiazhuang 050000, Hebei, China
    These authors contributed equally to this work.)

  • Yiyi Zhang

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, Guangxi University, Nanning 530004, Guangxi, China
    National Demonstration Center for Experimental Electrical Engineering Education, Guangxi University, Nanning 530004, Guangxi, China
    These authors contributed equally to this work.)

  • Yijie Ma

    (Shijiazhuang Power Supply Branch of State Grid Electric Power Company, Shijiazhuang 050000, Hebei, China)

  • Yang Shen

    (Shijiazhuang Power Supply Branch of State Grid Electric Power Company, Shijiazhuang 050000, Hebei, China)

  • Xiaochen Zhen

    (Shijiazhuang Power Supply Branch of State Grid Electric Power Company, Shijiazhuang 050000, Hebei, China)

  • Zilai Chen

    (Shijiazhuang Power Supply Branch of State Grid Electric Power Company, Shijiazhuang 050000, Hebei, China)

Abstract

The dielectric monitoring/diagnostic tool, such as Polarization and Depolarization Current (PDC) measurement, is now being widely applied to obtain the status of deteriorated transformers around the world. Nowadays, several works have reported that the chemical and electrical-based transformer insulation diagnostic parameters (absorption ratio, polarization index, paper conductivity, oil conductivity, insulation resistance, etc.) can be easily calculated from the PDC data. It is a fact that before using these parameters to obtain the status of deteriorated transformers, the power engineers should prudently investigate the effectiveness of these parameters. However, there are few papers that investigate the important issue. In addition, the understanding of temperature effect mechanism on these parameters should also be prudently studied. In the present work, we firstly prepare several oil-impregnated pressboard specimens with various insulation statuses by using a sequence of thermal ageing and moisture absorption experiments launched in the laboratory, and then the PDC measurement is performed to obtain the chemical and electrical-based transformer insulation diagnostic parameters. Finally, we systematically interpret the effectiveness and temperature effect mechanism on these chemical and electrical-based transformer insulation diagnostic parameters.

Suggested Citation

  • Hanbo Zheng & Jiefeng Liu & Yiyi Zhang & Yijie Ma & Yang Shen & Xiaochen Zhen & Zilai Chen, 2018. "Effectiveness Analysis and Temperature Effect Mechanism on Chemical and Electrical-Based Transformer Insulation Diagnostic Parameters Obtained from PDC Data," Energies, MDPI, vol. 11(1), pages 1-17, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:146-:d:125839
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    References listed on IDEAS

    as
    1. Yazid Hadjadj & Fethi Meghnefi & Issouf Fofana & Hassan Ezzaidi, 2013. "On the Feasibility of Using Poles Computed from Frequency Domain Spectroscopy to Assess Oil Impregnated Paper Insulation Conditions," Energies, MDPI, vol. 6(4), pages 1-17, April.
    2. Issouf Fofana & Yazid Hadjadj, 2016. "Electrical-Based Diagnostic Techniques for Assessing Insulation Condition in Aged Transformers," Energies, MDPI, vol. 9(9), pages 1-26, August.
    3. Jiefeng Liu & Hanbo Zheng & Yiyi Zhang & Hua Wei & Ruijin Liao, 2017. "Grey Relational Analysis for Insulation Condition Assessment of Power Transformers Based Upon Conventional Dielectric Response Measurement," Energies, MDPI, vol. 10(10), pages 1-16, October.
    4. Janvier Sylvestre N’cho & Issouf Fofana & Yazid Hadjadj & Abderrahmane Beroual, 2016. "Review of Physicochemical-Based Diagnostic Techniques for Assessing Insulation Condition in Aged Transformers," Energies, MDPI, vol. 9(5), pages 1-29, May.
    5. Abi Munajad & Cahyo Subroto & Suwarno, 2017. "Study on the Effects of Thermal Aging on Insulating Paper for High Voltage Transformer Composite with Natural Ester from Palm Oil Using Fourier Transform Infrared Spectroscopy (FTIR) and Energy Disper," Energies, MDPI, vol. 10(11), pages 1-15, November.
    6. Yiyi Zhang & Jiefeng Liu & Hanbo Zheng & Hua Wei & Ruijin Liao, 2017. "Study on Quantitative Correlations between the Ageing Condition of Transformer Cellulose Insulation and the Large Time Constant Obtained from the Extended Debye Model," Energies, MDPI, vol. 10(11), pages 1-17, November.
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    Citations

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    Cited by:

    1. Pawel Zukowski & Przemyslaw Rogalski & Konrad Kierczynski & Tomasz N. Koltunowicz, 2021. "Precise Measurements of the Temperature Influence on the Complex Permittivity of Power Transformers Moistened Paper-Oil Insulation," Energies, MDPI, vol. 14(18), pages 1-24, September.
    2. Konrad Kierczynski & Przemyslaw Rogalski & Vitalii Bondariev & Pawel Okal & Daniel Korenciak, 2022. "Research on the Influence of Moisture Exchange between Oil and Cellulose on the Electrical Parameters of the Insulating Oil in Power Transformers," Energies, MDPI, vol. 15(20), pages 1-15, October.
    3. Pawel Zukowski & Przemyslaw Rogalski & Tomasz N. Kołtunowicz & Konrad Kierczynski & Marek Zenker & Alexander D. Pogrebnjak & Matej Kucera, 2022. "DC and AC Tests of Moisture Electrical Pressboard Impregnated with Mineral Oil or Synthetic Ester—Determination of Water Status in Power Transformer Insulation," Energies, MDPI, vol. 15(8), pages 1-16, April.
    4. Fenglan Tian & Zhongzhao Jing & Huan Zhao & Enze Zhang & Jiefeng Liu, 2019. "A Synthetic Condition Assessment Model for Power Transformers Using the Fuzzy Evidence Fusion Method," Energies, MDPI, vol. 12(5), pages 1-17, March.
    5. Pawel Zukowski & Przemyslaw Rogalski & Vitalii Bondariev & Milan Sebok, 2022. "Diagnostics of High Water Content Paper-Oil Transformer Insulation Based on the Temperature and Frequency Dependencies of the Loss Tangent," Energies, MDPI, vol. 15(8), pages 1-16, April.
    6. Tomasz N. Kołtunowicz & Konrad Kierczynski & Pawel Okal & Aleksy Patryn & Miroslav Gutten, 2022. "Diagnostics on the Basis of the Frequency-Temperature Dependences of the Loss Angle Tangent of Heavily Moistured Oil-Impregnated Pressboard," Energies, MDPI, vol. 15(8), pages 1-14, April.

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