IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i9p2357-d168241.html
   My bibliography  Save this article

Simulation of Fluid-Thermal Field in Oil-Immersed Transformer Winding Based on Dimensionless Least-Squares and Upwind Finite Element Method

Author

Listed:
  • Gang Liu

    (Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University, Baoding 071003, China)

  • Zhi Zheng

    (Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University, Baoding 071003, China)

  • Dongwei Yuan

    (Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University, Baoding 071003, China)

  • Lin Li

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Changping District, Beijing 102206, China)

  • Weige Wu

    (Baoding Tianwei Baobian Electric Co., Ltd, Baoding 071056, China)

Abstract

In order to study the coupling fluid and thermal problems of the local winding in oil-immersed power transformers, the least-squares finite element method (LSFEM) and upwind finite element method (UFEM) are adopted, respectively, to calculate the fluid and thermal field in the oil duct. When solving the coupling problem by sequential iterations, the effect of temperature on the material property and the loss density of the windings should be taken into account. In order to improve the computation efficiency for the coupling fields, an algorithm, which adopts two techniques, the dimensionless LSFEM and the combination of Jacobi preconditioned conjugate gradient method (JPCGM) and the two-side equilibration method (TSEM), is proposed in this paper. To validate the efficiency of the proposed algorithm, a local winding model of a transformer is built and the fluid field is computed by the conventional LSFEM, dimensionless LSFEM, and the Fluent software. While the fluid and thermal computation results of the local winding model of a transformer obtained by the two LSFEMs are basically consistent with those of the Fluent software, the stiffness matrix, which is formed by the dimensionless scheme of LSFEM and preconditioned by the JPCGM and TSEM, has a smaller condition number and a faster convergence rate of the equations. Thus, it demonstrates a broader applicability.

Suggested Citation

  • Gang Liu & Zhi Zheng & Dongwei Yuan & Lin Li & Weige Wu, 2018. "Simulation of Fluid-Thermal Field in Oil-Immersed Transformer Winding Based on Dimensionless Least-Squares and Upwind Finite Element Method," Energies, MDPI, vol. 11(9), pages 1-17, September.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2357-:d:168241
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/9/2357/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/11/9/2357/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruohan Gong & Jiangjun Ruan & Jingzhou Chen & Yu Quan & Jian Wang & Cihan Duan, 2017. "Analysis and Experiment of Hot-Spot Temperature Rise of 110 kV Three-Phase Three-Limb Transformer," Energies, MDPI, vol. 10(8), pages 1-12, July.
    2. Radu Godina & Eduardo M. G. Rodrigues & João C. O. Matias & João P. S. Catalão, 2015. "Effect of Loads and Other Key Factors on Oil-Transformer Ageing: Sustainability Benefits and Challenges," Energies, MDPI, vol. 8(10), pages 1-40, October.
    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. Haonan Tian & Zhongbao Wei & Sriram Vaisambhayana & Madasamy Thevar & Anshuman Tripathi & Philip Kjær, 2019. "A Coupled, Semi-Numerical Model for Thermal Analysis of Medium Frequency Transformer," Energies, MDPI, vol. 12(2), pages 1-16, January.

    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. Miro Antonijević & Stjepan Sučić & Hrvoje Keserica, 2018. "Augmented Reality Applications for Substation Management by Utilizing Standards-Compliant SCADA Communication," Energies, MDPI, vol. 11(3), pages 1-17, March.
    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. 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.
    4. 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.
    5. Jun Jiang & Mingxin Zhao & Chaohai Zhang & Min Chen & Haojun Liu & Ricardo Albarracín, 2018. "Partial Discharge Analysis in High-Frequency Transformer Based on High-Frequency Current Transducer," Energies, MDPI, vol. 11(8), pages 1-13, August.
    6. Ruohan Gong & Jiangjun Ruan & Jingzhou Chen & Yu Quan & Jian Wang & Cihan Duan, 2017. "Analysis and Experiment of Hot-Spot Temperature Rise of 110 kV Three-Phase Three-Limb Transformer," Energies, MDPI, vol. 10(8), pages 1-12, July.
    7. 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.
    8. Zbigniew Nadolny, 2022. "Determination of Dielectric Losses in a Power Transformer," Energies, MDPI, vol. 15(3), pages 1-14, January.
    9. Álvaro Jaramillo-Duque & Nicolás Muñoz-Galeano & José R. Ortiz-Castrillón & Jesús M. López-Lezama & Ricardo Albarracín-Sánchez, 2018. "Power Loss Minimization for Transformers Connected in Parallel with Taps Based on Power Chargeability Balance," Energies, MDPI, vol. 11(2), pages 1-12, February.
    10. Haonan Tian & Zhongbao Wei & Sriram Vaisambhayana & Madasamy Thevar & Anshuman Tripathi & Philip Kjær, 2019. "A Coupled, Semi-Numerical Model for Thermal Analysis of Medium Frequency Transformer," Energies, MDPI, vol. 12(2), pages 1-16, January.
    11. Grzegorz Dombek & Zbigniew Nadolny & Piotr Przybylek & Radoslaw Lopatkiewicz & Agnieszka Marcinkowska & Lukasz Druzynski & Tomasz Boczar & Andrzej Tomczewski, 2020. "Effect of Moisture on the Thermal Conductivity of Cellulose and Aramid Paper Impregnated with Various Dielectric Liquids," Energies, MDPI, vol. 13(17), pages 1-17, August.
    12. Godina, Radu & Rodrigues, Eduardo M.G. & Matias, João C.O. & Catalão, João P.S., 2016. "Smart electric vehicle charging scheduler for overloading prevention of an industry client power distribution transformer," Applied Energy, Elsevier, vol. 178(C), pages 29-42.
    13. Zbigniew Nadolny & Grzegorz Dombek, 2018. "Electro-Insulating Nanofluids Based on Synthetic Ester and TiO 2 or C 60 Nanoparticles in Power Transformer," Energies, MDPI, vol. 11(8), pages 1-11, July.
    14. Piotr Przybylek, 2018. "A New Concept of Applying Methanol to Dry Cellulose Insulation at the Stage of Manufacturing a Transformer," Energies, MDPI, vol. 11(7), pages 1-13, June.
    15. Xiaojun Tang & Wenjing Wang & Xuliang Zhang & Erzhen Wang & Xuanjiannan Li, 2018. "On-Line Analysis of Oil-Dissolved Gas in Power Transformers Using Fourier Transform Infrared Spectrometry," Energies, MDPI, vol. 11(11), pages 1-15, November.
    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. Aya Amer & Khaled Shaban & Ahmed Gaouda & Ahmed Massoud, 2021. "Home Energy Management System Embedded with a Multi-Objective Demand Response Optimization Model to Benefit Customers and Operators," Energies, MDPI, vol. 14(2), pages 1-19, January.
    19. Bhaskar P. Rimal & Cuiyu Kong & Bikrant Poudel & Yong Wang & Pratima Shahi, 2022. "Smart Electric Vehicle Charging in the Era of Internet of Vehicles, Emerging Trends, and Open Issues," Energies, MDPI, vol. 15(5), pages 1-24, March.
    20. Dante Ruiz-Robles & Vicente Venegas-Rebollar & Adolfo Anaya-Ruiz & Edgar L. Moreno-Goytia & Juan R. Rodríguez-Rodríguez, 2018. "Design and Prototyping Medium-Frequency Transformers Featuring a Nanocrystalline Core for DC–DC Converters," Energies, MDPI, vol. 11(8), pages 1-17, August.

    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:9:p:2357-:d:168241. 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.