IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i18p3561-d268079.html
   My bibliography  Save this article

Modeling of the Winding Hot-Spot Temperature in Power Transformers: Case Study of the Low-Loaded Fleet

Author

Listed:
  • Michał Kunicki

    (Institute of Electrical Power Engineering and Renewable Energy, Opole University of Technology, 45-758 Opole, Poland)

  • Sebastian Borucki

    (Institute of Electrical Power Engineering and Renewable Energy, Opole University of Technology, 45-758 Opole, Poland)

  • Andrzej Cichoń

    (Institute of Electrical Power Engineering and Renewable Energy, Opole University of Technology, 45-758 Opole, Poland)

  • Jerzy Frymus

    (Tauron Dystrybucja S.A., 31-060 Kraków, Poland)

Abstract

A proposal of the dynamic thermal rating (DTR) applied and optimized for low-loaded power transformers equipped with on-line hot-spot (HS) measuring systems is presented in the paper. The proposed method concerns the particular population of mid-voltage (MV) to high-voltage (HV) transformers, a case study of the population of over 1500 units with low average load is analyzed. Three representative real-life working units are selected for the method evaluation and verification. Temperatures used for analysis were measured continuously within two years with 1 h steps. Data from 2016 are used to train selected models based on various machine learning (ML) algorithms. Data from 2017 are used to verify the trained models and to validate the method. Accuracy analysis of all applied ML algorithms is discussed and compared to the conventional thermal model. As a result, the best accuracy of the prediction of HS temperatures is yielded by a generalized linear model (GLM) with mean prediction error below 0.71% for winding HS. The proposed method may be implemented as a part of the technical assessment decision support systems and freely adopted for other electrical power apparatus after relevant data are provided for the learning process and as predictors for trained models.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3561-:d:268079
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/18/3561/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/18/3561/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stefan Tenbohlen & Sebastian Coenen & Mohammad Djamali & Andreas Müller & Mohammad Hamed Samimi & Martin Siegel, 2016. "Diagnostic Measurements for Power Transformers," Energies, MDPI, vol. 9(5), pages 1-25, May.
    2. 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.
    3. 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.
    4. Martin Siegel & Sebastian Coenen & Michael Beltle & Stefan Tenbohlen & Marc Weber & Pascal Fehlmann & Stefan M. Hoek & Ulrich Kempf & Robert Schwarz & Thomas Linn & Jitka Fuhr, 2019. "Calibration Proposal for UHF Partial Discharge Measurements at Power Transformers," Energies, MDPI, vol. 12(16), pages 1-17, August.
    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. 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.
    2. 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.

    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. 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.
    2. 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.
    3. Piotr Przybylek & Hubert Moranda & Hanna Moscicka-Grzesiak & Dominika Szczesniak, 2019. "Application of Synthetic Ester for Drying Distribution Transformer Insulation—The Influence of Cellulose Thickness on Drying Efficiency," Energies, MDPI, vol. 12(20), pages 1-16, October.
    4. Wojciech Sikorski & Krzysztof Walczak & Piotr Przybylek, 2016. "Moisture Migration in an Oil-Paper Insulation System in Relation to Online Partial Discharge Monitoring of Power Transformers," Energies, MDPI, vol. 9(12), pages 1-16, December.
    5. 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.
    6. Issouf Fofana & Yazid Hadjadj, 2018. "Power Transformer Diagnostics, Monitoring and Design Features," Energies, MDPI, vol. 11(12), pages 1-5, November.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Sergio Bustamante & Mario Manana & Alberto Arroyo & Raquel Martinez & Alberto Laso, 2020. "A Methodology for the Calculation of Typical Gas Concentration Values and Sampling Intervals in the Power Transformers of a Distribution System Operator," Energies, MDPI, vol. 13(22), pages 1-18, November.
    17. 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.
    18. 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.
    19. Tomasz Piotrowski & Pawel Rozga & Ryszard Kozak, 2019. "Comparative Analysis of the Results of Diagnostic Measurements with an Internal Inspection of Oil-Filled Power Transformers," Energies, MDPI, vol. 12(11), pages 1-18, June.
    20. 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.

    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:12:y:2019:i:18:p:3561-:d:268079. 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.