A Winding Temperature Rise Prediction Method for Oil-Immersed Distribution Transformers Using Thermal Circuit Model Parameter Identification

WEN Guohao; LI Jialing; ZHANG Fan; ZHANG Hebin; CHEN Hongtao; ZHENG Zhiyao; YU Congwei; HU Yujia; JI Shengchang

doi:10.7652/xjtuxb202605020

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A Winding Temperature Rise Prediction Method for Oil-Immersed Distribution Transformers Using Thermal Circuit Model Parameter Identification

更新时间：2026-04-27

- A Winding Temperature Rise Prediction Method for Oil-Immersed Distribution Transformers Using Thermal Circuit Model Parameter Identification
- Journal of Xi'an Jiaotong University Vol. 60, Issue 5, Pages: 206-216(2026)
- 作者机构：
  
  西安交通大学电力设备电气绝缘国家重点实验室，710049，西安
  浙江华电器材检测研究院有限公司配网设备研究所，310022，杭州
  南京工程学院电气工程学院，210000，南京
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202605020
  CLC： TM411.2
- Received：21 July 2025，
  
  Published：10 May 2026
- 稿件说明：
移动端阅览
WEN Guohao, LI Jialing, ZHANG Fan, et al. A Winding Temperature Rise Prediction Method for Oil-Immersed Distribution Transformers Using Thermal Circuit Model Parameter Identification[J]. Journal of Xi'an Jiaotong University, 2026, 60(5): 206-216.
DOI：

WEN Guohao, LI Jialing, ZHANG Fan, et al. A Winding Temperature Rise Prediction Method for Oil-Immersed Distribution Transformers Using Thermal Circuit Model Parameter Identification[J]. Journal of Xi'an Jiaotong University, 2026, 60(5): 206-216. DOI： 10.7652/xjtuxb202605020.

摘要

为解决油浸式配电变压器温升试验时间长、效率低的问题，提出了一种采用热路模型参数辨识预测油浸式配电变压器绕组温升的方法。基于热电类比原理，构建包含铁芯和高、低压绕组损耗的油浸式配电变压器5阶热路模型。为获得热路参数，该研究引入扩展卡尔曼滤波算法，结合5阶热路模型并利用2h实测数据，实现对热路参数的动态辨识。通过数值求解得到顶层油，高、低压绕组温升曲线，实现温升预测的目的。研

究结果表明：辨识得到400 kV·A变压器的低压绕组、高压绕组、油和油箱的热容分别约为66.1、110.1、255.7和125.6 kJ·K

-1

，低压绕组-油、高压绕组-油、油-油箱、油箱-空气的热阻分别约为8.76、6.61、0.56和10.96 mK·W

-1

，各参数波动范围小于10%；高压绕组-油热阻随变压器容量的提高显著降低，400 kV·A时为6.61 mK·W

-1

，800 kV·A时降至4.00 mK·W

-1

；额定损耗功率下，400、630及800 kV·A变压器顶层油稳态温升预测的相对误差最大值为4.86%，最大绝对误差为2.6 K；基于不同损耗功率下的预测结果表明，1.0倍总损耗功率下的预测误差低于2 K，0.5倍总损耗功率下因参数在低温升区间的非线性偏移，误差增至7.3 K。所提方法可用于油浸式配电变压器温升的快速检测与评估。

Abstract

To address the issues of long temperature rise time and low efficiency in oil-immersed distribution transformers

a method for predicting winding temperature rise in such transformers using thermal circuit model parameter identification is proposed. Based on the principle of thermal-electrical analogy

a fifth-order thermal circuit model for oil-immersed distribution transformers was established

which includes losses from the core and both high-voltage and low voltage windings. To obtain the thermal parameters

an extended Kalman filter algorithm was introduced to achieve dynamic identification of the thermal circuit parameters by integrating the fifth-order thermal circuit model with 2 h of measured data. Numerical solutions were used to calculate the temperature rise curves of the top oil and the high-and low-voltage windings

achieving the goal of temperature rise prediction. The results show that the identified thermal capacitances for the low-voltage winding

high-voltage winding

oil

and tank of a 400 kV·A transformer are approximately 66.1

110.1

255.7

and 125.6 kJ·K

-1

respectively

while the thermal resistances for the low-voltage winding-oil

high-voltage winding-oil

oil-tank

and tankair are approximately 8.76

6.61

0.56

and 10.96 mK·W

-1

respectively

with fluctuations in each parameter being less than 10%. The thermal resistance between the high-voltage winding and oil significantly decreases with increasing transformer capacity

dropping from 6.61 mK·W

-1

at 400 kV·A to 4.00

mK·W

-1

at 800 kV·A. Under rated loss power

the maximum relative error in predicting the steady-state temperature rise of the top oil for 400

630

and 800 kV·A transformers is 4.86%

with a maximum absolute error of 2.6 K. Prediction results under different loss power levels indicate that the prediction accuracy under 1.0 times the total loss power is below 2 K

while under 0.5 times the total loss power

nonlinear parameter drift at low temperature rise leads to an increased error of up to 7.3 K. The proposed method can be used for rapid temperature rise detection and assessment of oil-immersed distribution transformers.

关键词

Keywords

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