IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i2p429-d1319875.html
   My bibliography  Save this article

Innovative Transformer Life Assessment Considering Moisture and Oil Circulation

Author

Listed:
  • Zhengping Liang

    (North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Beijing 100120, China)

  • Yan Fang

    (North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Beijing 100120, China)

  • Hao Cheng

    (North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Beijing 100120, China)

  • Yongbin Sun

    (North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Beijing 100120, China)

  • Bo Li

    (Guangxi Power Transmission and Distribution Network Lightning Protection Engineering Technology Research Center, Guangxi University, Nanning 530004, China)

  • Kai Li

    (North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Beijing 100120, China)

  • Wenxuan Zhao

    (North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Beijing 100120, China)

  • Zhongxu Sun

    (North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group, Beijing 100120, China)

  • Yiyi Zhang

    (Guangxi Power Transmission and Distribution Network Lightning Protection Engineering Technology Research Center, Guangxi University, Nanning 530004, China)

Abstract

Power transformers are one of the most expensive and important equipment in the power system. Significant differences exist in the insulation lifespan of transformers that have been in operation for more than 20 years, and using identical maintenance or scrapping methods may result in significant economic losses. However, most existing transformer life assessment methods only consider the impact of moisture content on the life decay rate without considering the impact of oil circulation cooling modes, which leads to some evaluation errors. In this study, we established a new transformer life assessment method that considers the influence of moisture content and oil circulation cooling modes, which is more accurate than most life assessment methods. Then, the proposed life evaluation method was validated on the on-site transformers, demonstrating its accuracy and effectiveness. The novelty of this study is that it establishes a new on-site transformer life assessment method that considers the comprehensive effect of moisture content and oil circulation cooling mode, which helps to evaluate the remaining lifespan of power transformers more accurately and thus extends the transformer lifespan systematically.

Suggested Citation

  • Zhengping Liang & Yan Fang & Hao Cheng & Yongbin Sun & Bo Li & Kai Li & Wenxuan Zhao & Zhongxu Sun & Yiyi Zhang, 2024. "Innovative Transformer Life Assessment Considering Moisture and Oil Circulation," Energies, MDPI, vol. 17(2), pages 1-21, January.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:2:p:429-:d:1319875
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/2/429/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/2/429/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    Full references (including those not matched with items on IDEAS)

    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. Dias, Luis & Leitão, Armando & Guimarães, Luis, 2021. "Resource definition and allocation for a multi-asset portfolio with heterogeneous degradation," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    2. Huang, Wei & Shao, Changzheng & Hu, Bo & Li, Weizhan & Sun, Yue & Xie, Kaigui & Zio, Enrico & Li, Wenyuan, 2023. "A restoration-clustering-decomposition learning framework for aging-related failure rate estimation of distribution transformers," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    3. Aizpurua, J.I. & Stewart, B.G. & McArthur, S.D.J. & Penalba, M. & Barrenetxea, M. & Muxika, E. & Ringwood, J.V., 2022. "Probabilistic forecasting informed failure prognostics framework for improved RUL prediction under uncertainty: A transformer case study," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Enze Zhang & Jiang Liu & Chaohai Zhang & Peijun Zheng & Yosuke Nakanishi & Thomas Wu, 2023. "State-of-Art Review on Chemical Indicators for Monitoring the Aging Status of Oil-Immersed Transformer Paper Insulation," Energies, MDPI, vol. 16(3), pages 1-31, January.

    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:17:y:2024:i:2:p:429-:d:1319875. 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.