IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i1p146-d125839.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/1/146/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/1/146/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    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. 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.

    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. Jiake Fang & Hanbo Zheng & Jiefeng Liu & Junhui Zhao & Yiyi Zhang & Ke Wang, 2018. "A Transformer Fault Diagnosis Model Using an Optimal Hybrid Dissolved Gas Analysis Features Subset with Improved Social Group Optimization-Support Vector Machine Classifier," Energies, MDPI, vol. 11(8), pages 1-18, July.
    2. Feng Yang & Lin Du & Lijun Yang & Chao Wei & Youyuan Wang & Liman Ran & Peng He, 2018. "A Parameterization Approach for the Dielectric Response Model of Oil Paper Insulation Using FDS Measurements," Energies, MDPI, vol. 11(3), pages 1-17, March.
    3. Leila Safiddine & Hadj-Ziane Zafour & Ungarala Mohan Rao & Issouf Fofana, 2019. "Regeneration of Transformer Insulating Fluids Using Membrane Separation Technology," Energies, MDPI, vol. 12(3), pages 1-13, January.
    4. 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.
    5. Issouf Fofana & Yazid Hadjadj, 2018. "Power Transformer Diagnostics, Monitoring and Design Features," Energies, MDPI, vol. 11(12), pages 1-5, November.
    6. Janvier Sylvestre N’cho & Issouf Fofana, 2020. "Review of Fiber Optic Diagnostic Techniques for Power Transformers," Energies, MDPI, vol. 13(7), pages 1-24, April.
    7. Siti Rosilah Arsad & Pin Jern Ker & Md. Zaini Jamaludin & Pooi Ying Choong & Hui Jing Lee & Vimal Angela Thiviyanathan & Young Zaidey Yang Ghazali, 2023. "Water Content in Transformer Insulation System: A Review on the Detection and Quantification Methods," Energies, MDPI, vol. 16(4), pages 1-31, February.
    8. Andrew Adewunmi Adekunle & Samson Okikiola Oparanti & Issouf Fofana, 2023. "Performance Assessment of Cellulose Paper Impregnated in Nanofluid for Power Transformer Insulation Application: A Review," Energies, MDPI, vol. 16(4), pages 1-32, February.
    9. Chenmeng Zhang & Kailin Zhao & Shijun Xie & Can Hu & Yu Zhang & Nanxi Jiang, 2021. "Research on the Time-Domain Dielectric Response of Multiple Impulse Voltage Aging Oil-Film Dielectrics," Energies, MDPI, vol. 14(7), pages 1-15, April.
    10. 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.
    11. 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.
    12. Zhilin Lyu & Qing Wei & Yiyi Zhang & Junhui Zhao & Emad Manla, 2018. "Adaptive Virtual Impedance Droop Control Based on Consensus Control of Reactive Current," Energies, MDPI, vol. 11(7), pages 1-17, July.
    13. Jingxin Zou & Weigen Chen & Fu Wan & Zhou Fan & Lingling Du, 2016. "Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers," Energies, MDPI, vol. 9(11), pages 1-14, November.
    14. Wojciech Sikorski, 2018. "Active Dielectric Window: A New Concept of Combined Acoustic Emission and Electromagnetic Partial Discharge Detector for Power Transformers," Energies, MDPI, vol. 12(1), pages 1-27, December.
    15. Amidou Betie & Fethi Meghnefi & Issouf Fofana & Zie Yeo, 2018. "Modeling the Insulation Paper Drying Process from Thermogravimetric Analyses," Energies, MDPI, vol. 11(3), pages 1-15, February.
    16. 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.
    17. Nuria Novas & Alfredo Alcayde & Isabel Robalo & Francisco Manzano-Agugliaro & Francisco G. Montoya, 2020. "Energies and Its Worldwide Research," Energies, MDPI, vol. 13(24), pages 1-41, December.
    18. 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.
    19. Guoqiang Xia & Guangning Wu & Bo Gao & Haojie Yin & Feibao Yang, 2017. "A New Method for Evaluating Moisture Content and Aging Degree of Transformer Oil-Paper Insulation Based on Frequency Domain Spectroscopy," Energies, MDPI, vol. 10(8), pages 1-15, August.
    20. Qing Yang & Peiyu Su & Yong Chen, 2017. "Comparison of Impulse Wave and Sweep Frequency Response Analysis Methods for Diagnosis of Transformer Winding Faults," Energies, MDPI, vol. 10(4), pages 1-16, March.

    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:11:y:2018:i:1:p:146-:d:125839. 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.