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Reliability Evaluation Method for Oil–Paper Insulation in Power Transformers

Author

Listed:
  • Youyuan Wang

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China
    High Voltage Laboratory, Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA)

  • Senlian Gong

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China)

  • Stanislaw Grzybowski

    (High Voltage Laboratory, Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS 39762, USA)

Abstract

The overall life of oil-immersed power transformers depends on the long-term life of the oil–paper insulation system throughout continuous operation. Studying the reliability assessment methods for oil–paper insulation can help determine the reliability level of power transformers accurately, and ensure their safe and stable operation. In the present paper, the life of oil–paper insulation is proven to obey the Weibull distribution under eight different temperatures set by the Weibull reliability probability paper; the failure mechanisms of the different temperatures are highly consistent. The Weibull distribution reliability curve cluster of oil–paper insulation is plotted under different temperatures by which an oil–paper insulation reliability assessment method is proposed. Lastly, the statistical validation experiment of the proposed method is conducted, which proves its theoretical validity. Thus, the present study puts forward a simple and effective method for the oil–paper insulation reliability assessment of power transformers under different temperatures at different life stages.

Suggested Citation

  • Youyuan Wang & Senlian Gong & Stanislaw Grzybowski, 2011. "Reliability Evaluation Method for Oil–Paper Insulation in Power Transformers," Energies, MDPI, vol. 4(9), pages 1-14, September.
    • Handle: RePEc:gam:jeners:v:4:y:2011:i:9:p:1362-1375:d:13900
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    Citations

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    Cited by:

    1. Jing Wu & Kun Li & Jing Sun & Li Xie, 2018. "A Novel Integrated Method to Diagnose Faults in Power Transformers," Energies, MDPI, vol. 11(11), pages 1-8, November.
    2. Lefeng Cheng & Tao Yu & Guoping Wang & Bo Yang & Lv Zhou, 2018. "Hot Spot Temperature and Grey Target Theory-Based Dynamic Modelling for Reliability Assessment of Transformer Oil-Paper Insulation Systems: A Practical Case Study," Energies, MDPI, vol. 11(1), pages 1-26, January.
    3. Lefeng Cheng & Tao Yu, 2018. "Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey," Energies, MDPI, vol. 11(4), pages 1-69, April.
    4. Hongyan Nie & Xinlao Wei & Yonghong Wang & Qingguo Chen, 2018. "A Study of Electrical Aging of the Turn-to-Turn Oil-Paper Insulation in Transformers with a Step-Stress Method," Energies, MDPI, vol. 11(12), pages 1-16, November.
    5. Ariannik, Mohamadreza & Razi-Kazemi, Ali A. & Lehtonen, Matti, 2020. "An approach on lifetime estimation of distribution transformers based on degree of polymerization," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    6. 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.
    7. Issouf Fofana & John Sabau & Amidou Betie, 2015. "Measurement of the Relative Free Radical Content of Insulating Oils of Petroleum Origin," Energies, MDPI, vol. 8(8), pages 1-13, July.
    8. Sýkora, Miroslav & Marková, Jana & Diamantidis, Dimitris, 2018. "Bayesian network application for the risk assessment of existing energy production units," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 312-320.

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