Research on temperature distribution characteristics of oil‐immersed power transformers based on fluid network decoupling

Abstract Due to the complex structure and large size of large‐capacity oil‐immersed power transformers, it is difficult to predict the winding temperature distribution directly by numerical analysis. A 180 MVA, 220 kV oil‐immersed self‐cooling power transformer is used as the research object. The authors decouple the internal fluid domain of the power transformer into four regions: high voltage windings, medium voltage windings, low voltage windings, and radiators through fluid networks and establish the 3D fluid‐temperature field numerical analysis model of the four regions, respectively. The results of the fluid network model are used as the inlet boundary conditions for the 3D fluid‐temperature numerical analysis model. In turn, the fluid resistance of the fluid network model is corrected according to the results of the 3D fluid‐temperature field numerical analysis model. The prediction of the temperature distribution of windings is realised by the coupling calculation between the fluid network model and the 3D fluid‐temperature field numerical analysis model. Based on this, the effect of the loading method of the heat source is also investigated using the proposed method. The hotspot temperatures of the high‐voltage, medium‐voltage, and low‐voltage windings are 89.43, 86.33, and 80.96°C, respectively. Finally, an experimental platform is built to verify the results. The maximum relative error between calculated and measured values is 4.42%, which meets the engineering accuracy requirement.

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Publication Details

Journal
High Voltage
Published
2024-09-27
DOI
https://doi.org/10.1049/hve2.12488
Citations
6
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
1.25

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article

Research on temperature distribution characteristics of oil‐immersed power transformers based on fluid network decoupling

Ziyi Xu, Yongming Xu, Yaodong Wang, Congrui Ren
6 citations
High Voltage
Power Transformer Diagnostics and Insulation
1.25
article

Research on temperature distribution characteristics of oil‐immersed power transformers based on fluid network decoupling

Ziyi Xu, Yongming Xu, Yaodong Wang, Congrui Ren
article en
6 citations

Abstract

Abstract Due to the complex structure and large size of large‐capacity oil‐immersed power transformers, it is difficult to predict the winding temperature distribution directly by numerical analysis. A 180 MVA, 220 kV oil‐immersed self‐cooling power transformer is used as the research object. The authors decouple the internal fluid domain of the power transformer into four regions: high voltage windings, medium voltage windings, low voltage windings, and radiators through fluid networks and establish the 3D fluid‐temperature field numerical analysis model of the four regions, respectively. The results of the fluid network model are used as the inlet boundary conditions for the 3D fluid‐temperature numerical analysis model. In turn, the fluid resistance of the fluid network model is corrected according to the results of the 3D fluid‐temperature field numerical analysis model. The prediction of the temperature distribution of windings is realised by the coupling calculation between the fluid network model and the 3D fluid‐temperature field numerical analysis model. Based on this, the effect of the loading method of the heat source is also investigated using the proposed method. The hotspot temperatures of the high‐voltage, medium‐voltage, and low‐voltage windings are 89.43, 86.33, and 80.96°C, respectively. Finally, an experimental platform is built to verify the results. The maximum relative error between calculated and measured values is 4.42%, which meets the engineering accuracy requirement.

High VoltageVol. 9(5)
Harbin University of Science and Technology (CN), Durham University (GB), Changzhou Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 20%
Power Transformer Diagnostics and Insulation
1.25
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