Numerical Prediction of Losses and Local Overheating in Transformer Windings Based on Magnetic-Thermal-Fluid Model
Li Yongjian1,2, Yan Xinxiao1,2, Zhang Changgeng1,2, Chen Yifan1,2, Ying Wenliang3
1. Hebei Province Key Laboratory of EFEAR Hebei University of Technology Tianjin 300130 China; 2. State Key Laboratory of EERI Hebei University of Technology Tianjin 300130 China; 3. TBEA Tianjin Transformers Co. Ltd Tianjin 300450 China
Abstract：Based on finite element method, the 3-D transient electromagnetic field simulation of a 2500kV•A dry-type transformer under rated load condition is carried out. The effect of the leakage flux on the eddy current distribution in foil windings and structures is considered in the calculation. The magneto-thermal-fluid coupling model was established and the loss density on each mesh element was mapped into the 3-D thermal field as heat sources. Considering the influence of temperature on material loss characteristics, the convective heat transfer process is accurately simulated, and the calculation of transformer temperature rise and the prediction of winding hot spots are realized. The test of transformer temperature rise indicated that the error between the predicted value of the model and test results was controlled within ± 6%. The temperature rise distribution law was in good agreement with actual situation. The multi-physics two-way coupling anlysis method adopted in this paper overcomes the inaccurate of loss calculation by the traditional magnetic circuit method. It can provide loss prediction methods and calculation data at the initial stage of transformer product development, and significantly improve the operating efficiency of related electrical equipment.
李永建, 闫鑫笑, 张长庚, 陈怡帆, 盈文亮. 基于磁-热-流耦合模型的变压器损耗计算和热点预测[J]. 电工技术学报, 2020, 35(21): 4483-4491.
Li Yongjian, Yan Xinxiao, Zhang Changgeng, Chen Yifan, Ying Wenliang. Numerical Prediction of Losses and Local Overheating in Transformer Windings Based on Magnetic-Thermal-Fluid Model. Transactions of China Electrotechnical Society, 2020, 35(21): 4483-4491.
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2020, Vol. 35 
