IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i9p3379-d809496.html
   My bibliography  Save this article

Oil-Immersed Power Transformer Condition Monitoring Methodologies: A Review

Author

Listed:
  • Lan Jin

    (School of Electrical Engineering, Computing, Mathematical Sciences, Curtin University, Perth, WA 6845, Australia)

  • Dowon Kim

    (School of Electrical Engineering, Computing, Mathematical Sciences, Curtin University, Perth, WA 6845, Australia)

  • Ahmed Abu-Siada

    (School of Electrical Engineering, Computing, Mathematical Sciences, Curtin University, Perth, WA 6845, Australia)

  • Shantanu Kumar

    (BHP, Perth, WA 6000, Australia)

Abstract

A power transformer is one of the most critical and expensive assets in electric power systems. Failure of a power transformer would not only result in a downtime to the entire transmission and distribution networks but may also cause personnel and environmental hazards due to oil leak and fire. Hence, to enhance a transformer’s reliability and extend its lifespan, a cost-effective and reliable condition monitoring technique should be adopted from day one of its installation. This will help detect incipient faults, extend a transformer’s operational life, and avoid potential consequences. With the global trend to establish digital substation automation systems, transformer online condition monitoring has been given much attention by utilities and researchers alike. Several online and offline condition monitoring techniques have been recently proposed for oil-immersed power transformers. This paper is aimed at providing a state-of-the-art review for the various condition monitoring technologies used for oil-immersed power transformers. Concept of measurements and analysis of the results along with the future trend of condition monitoring techniques are presented.

Suggested Citation

  • Lan Jin & Dowon Kim & Ahmed Abu-Siada & Shantanu Kumar, 2022. "Oil-Immersed Power Transformer Condition Monitoring Methodologies: A Review," Energies, MDPI, vol. 15(9), pages 1-32, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3379-:d:809496
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/9/3379/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/9/3379/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ahmed Abu-Siada, 2019. "Improved Consistent Interpretation Approach of Fault Type within Power Transformers Using Dissolved Gas Analysis and Gene Expression Programming," Energies, MDPI, vol. 12(4), pages 1-13, February.
    2. 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.
    3. Ji Liu & Daning Zhang & Xinlao Wei & Hamid Reza Karimi, 2014. "Transformation Algorithm of Dielectric Response in Time-Frequency Domain," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-7, June.
    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. Sun, YongTeng & Ma, HongZhong, 2024. "Research progress on oil-immersed transformer mechanical condition identification based on vibration signals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 196(C).

    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. Alper Aydogan & Fatih Atalar & Aysel Ersoy Yilmaz & Pawel Rozga, 2020. "Using the Method of Harmonic Distortion Analysis in Partial Discharge Assessment in Mineral Oil in a Non-Uniform Electric Field," Energies, MDPI, vol. 13(18), pages 1-18, September.
    2. 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.
    3. 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.
    4. Jaroslaw Krzywanski, 2022. "Advanced AI Applications in Energy and Environmental Engineering Systems," Energies, MDPI, vol. 15(15), pages 1-3, August.
    5. Ancuța-Mihaela Aciu & Claudiu-Ionel Nicola & Marcel Nicola & Maria-Cristina Nițu, 2021. "Complementary Analysis for DGA Based on Duval Methods and Furan Compounds Using Artificial Neural Networks," Energies, MDPI, vol. 14(3), pages 1-22, January.
    6. Bing Zeng & Jiang Guo & Wenqiang Zhu & Zhihuai Xiao & Fang Yuan & Sixu Huang, 2019. "A Transformer Fault Diagnosis Model Based On Hybrid Grey Wolf Optimizer and LS-SVM," Energies, MDPI, vol. 12(21), pages 1-18, November.

    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:15:y:2022:i:9:p:3379-:d:809496. 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.