Research on the prediction method of winding temperature rise of oil-immersed distribution transformer based on the identification of thermal circuit model parameters

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

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Research on the prediction method of winding temperature rise of oil-immersed distribution transformer based on the identification of thermal circuit model parameters

更新时间：2026-01-02

- Research on the prediction method of winding temperature rise of oil-immersed distribution transformer based on the identification of thermal circuit model parameters
- JOURNAL OF XI’AN JIAOTONG UNIVERSITY (2026)
- 作者机构：
  
  1.西安交通大学电力设备电气绝缘国家重点实验室，710049，陕西西安
  2.浙江华电器材检测研究院有限公司，310022，浙江杭州
  3.南京工程学院，210000，江苏南京
- 作者简介：
- 基金信息：
- DOI：
  CLC： TM411+.2
- Received：21 July 2025，
  
  Revised：2025-08-29，
  
  Accepted：25 September 2025，
- 稿件说明：
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WEN Guohao, LI Jialing, ZHANG Fan, et al. Research on the prediction method of winding temperature rise of oil-immersed distribution transformer based on the identification of thermal circuit model parameters[J/OL]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY, 2026.
DOI：

WEN Guohao, LI Jialing, ZHANG Fan, et al. Research on the prediction method of winding temperature rise of oil-immersed distribution transformer based on the identification of thermal circuit model parameters[J/OL]. JOURNAL OF XI’AN JIAOTONG UNIVERSITY, 2026. DOI：

摘要

油浸式配电变压器温升试验耗时数十小时，耗能大且检测效率低。为了缩短温升试验时长提高效率，本文提出了一种基于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，通过构建油浸式配电变压器温升的5阶热路模型，基于扩展卡尔曼滤波算法对2小时实测数据进行热路模型热容、热阻参数辨识，最后计算得出油顶层、高低压绕组温升曲线，从而实现油浸式配电变压器稳态温升预测，达到变压器温升快速检测的目的。研究结果表明：辨识得到400 kVA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 kJ/K、110.1kJ/K、255.7 kJ/K和125.6 kJ/K，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 mK/W、6.61mK/W、0.56mK/W和10.96mK/W，各参数波动范围<10%；随变压器容量提高，高压绕组对油热阻从400kVA容量的6.61mK/W降低至800kVA容量的4.00 mK/W；额定损耗功率下，400kVA、630kVA及800kVA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℃；基于不同损耗功率下的预测结果表明，1倍总损下辨识参数后的预测精度低于2℃，0.5倍总损下参数在低温升下的非线性偏移，误差增至7.3℃。本文所提出的方法可用于油浸式配电变压器温升的快速检测与评估。

Abstract

Temperature rise tests for oil-immersed distribution transformers take dozens of hours

consume a lot of energy

and are not very efficient. To reduce the time required for these tests and improve efficiency

this paper proposes a temperature rise prediction method for oil-immersed distribution transformer windings based on thermal circuit model parameter identification. First

a fifth-order thermal circuit model is constructed for the temperature rise of oil-immersed distribution transformers. Then

the thermal capacity and thermal resistance parameters of the thermal circuit model are identified using the extended Kalman filter algorithm with two hours of actual measurement data. Finally

Finally

the temperature rise curves for the top oil layer and high/low-voltage windings are calculated

enabling the prediction of steady-state temperature rise for oil-immersed distribution transformers and the rapid detection of transformer temperature rise. The extant research findings indicate the following: The identified thermal capacities of the low-voltage winding

high-voltage winding

oil

and oil tank for a 400 kVA transformer are approximately 66.1 kJ/K

110.1 kJ/K

255.7 kJ/K

and 125.6 kJ/K

respectively. The thermal resistances between the low-voltage winding-oil

high-voltage winding-oil

oil-oil tank

and tank-to-air thermal resistance are approximately 8.76 mK/W

6.61 mK/W

0.56 mK/W

and 10.96 mK/W

respectively

with parameter fluctuations less than 10%. As transformer capacity increases

the thermal resistance between the high-voltage winding and oil decreases from 6.61 mK/W at 400kVA to 4.00 mK/W at 800kVA. At rated loss power

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

630kVA

and 800kVA transformers is 4.86%

with a maximum absolute error of 2.6°C. The prediction results under varying loss power conditions suggest that the prediction accuracy following parameter identification is less than 2°C at 1 times total loss. At 0.5 times total loss

the nonlinear offset of parameters under low temperature rise increases the error to 7.3°C. The proposed method has the potential for application in the rapid detection and evaluation of temperature rise in oil-immersed distribution transformers.

关键词

Keywords

references

LIN L , QIANG C , ZHANG H , et al . Review of studies on the hot spot temperature of oil-immersed transformers [J ] . Energies , 2024 , 18 ( 1 ): 74 .

WEN Q , ZHANG B , HE Z , et al . Simulation and analysis of oil-immersed transformer based on thermal-fluid coupled field [J ] . International Conference on Power System Technology , 2014 .

刘刚 , 胡万君 , 郝世缘 , 等 . 油浸式变压器绕组瞬态温升降阶快速计算方法 [J ] . 电工技术学报 , 2024 , 39 ( 03 ): 643 - 657 .

LIU Gang , HU Wanjun , HAO Shiyuan , et al . Reduced Order Calculation Method of Steady Temperature Rise of Oil Immersed Power Transformer [J ] . Transactions of China Electrotechnical Society , 2024 , 39 ( 03 ): 643 - 657 .

俞潺潺 . 大型油浸式自冷变压器温升的研究 [D ] . 浙江工业大学 , 2014 .

YU Chanchan . Research of large oil-immersed self-cooled transformer temperature rise [D ] . Zhejiang University of Technology , 2014 .

袁小娴 , 马桂芬 . 油浸式电力变压器非额定条件下的温升试验研究 [J ] . 电工材料 , 2016 , ( 05 ): 25 - 27 .

YUAN Xxiaoxian , MA Guifen . Temperature Rise Study for Oil-immersed Transformer under Non-nominal Conditions [J ] . Electrical Engineering Materials , 2016 , ( 05 ): 25 - 27 .

WANG Q Y , YU X , PENG Z , et al . 3D coupled electromagnetic-thermal-fluid method for computation of temperature field of converter transformer RIP bushings [J ] . Proceedings of the CSEE , 2016 , 36 ( 22 ): 6334 - 6341 .

丁玉琴 , 张乔根 , 高萌 , 等 . 油浸式配电变压器分布式热路模型 [J ] . 高电压技术 , 2019 , 45 ( 03 ): 968 - 974 .

DING Yuqing , ZHANG Qiaogen , GAO Men , et al . Distributed Thermal Circuit Model of Oil-immersed Distribution Transformers [J ] . High Voltage Engineering , 2019 , 45 ( 03 ): 968 - 974 .

SUSA D , LEHTONEN M , NORDMAN H . Dynamic thermal modelling of power transformers [J ] . IEEE Transactions on Power Delivery , 2005 , 20 ( 1 ): 197 - 204 .

SWIFT G , MOLINSKI T S , LEHN W . A fundamental approach to transformer thermal modeling. I. Theory and equivalent circuit [J ] . IEEE Transactions on Power Delivery , 2002 , 16 ( 2 ): 171 - 175 .

GERLING D , DAJAKU G . Novel lumped-parameter thermal model for electrical systems [C ] // European Conference on Power Electronics and Applications . IEEE , 2006 .

LI H , LIU Y , ZHUANG X , et al . Test and analysis on extended temperature rise of 110 kV transformer based on distributed temperature sensing [J ] . IEEE Transactions on Power Delivery , 2023 , 38 ( 2 ): 12 .

王红英 . 基于荧光光纤传感的油浸式变压器绕组测温研究 [J ] . 西安文理学院学报: 自然科学版 , 2018 , 21 ( 2 ): 5 .

WANG Hongying . Research on Temperature Measurement of Oil Immersed Transformer Windings Based on Fluorescent Optical Fiber Sensing [J ] . Journal of Xi'an University of Arts and Science (Natural Science Edition) , 2018 , 21 ( 2 ): 5 .

邓建钢 , 郭涛 , 徐秋元 , 等 . 变压器绕组测温光纤光栅传感器设计及性能测试 [J ] . 高电压技术 , 2012 , 38 ( 6 ): 8 .

DENG Jiangang , GUO Tao , XU Qiuyuan , et al . Design and Performance Test for Fiber Bragg Grating Sensors of Transformer Winding Temperature Measurement [J ] . High Voltage Engineering , 2012 , 38 ( 6 ): 8 .

贾红元 , 冀增华 , 李彬 , 等 . 变压器绕组温度的软件计算值与光纤实测值之间的差异对比分析 [J ] . 变压器 , 2014 , 51 ( 4 ): 4 .

JIA Hongyuan , JI Zenghua , LI Bin , et al . Comparative Analysis of Value Differences Between Software Calculation and Optical Fibre Measurement of Transformer Winding Temperature [J ] . Transformer , 2014 , 51 ( 4 ): 4 .

王恩 , 赵振刚 , 曹敏 , 等 . 基于光纤Bragg光栅的油浸式变压器多点温度监测 [J ] . 高电压技术 , 2017 , 043 ( 005 ): 1543 - 1549 .

WANG En , ZHAO Zhengang , CAO Min , et al . Multi Point Temperature Monitoring of Oil Immersed Transformer Based on Fiber Bragg Grating [J ] . High Voltage Engineering , 2017 , 43 ( 5 ): 1543 - 1549 .

LIU Y , LI X , LI H , et al . Experimental and numerical investigation of the internal temperature of an oil-immersed power transformer with DOFS [J ] . Applied Sciences , 2020 , 10 ( 16 ): 5718 .

刘鉴民 . 传热传质原理及其在电力科技中的应用 [M ] . 北京：中国电力出版社， 2006 : 137 - 140 .

LIU Jianmin . Principles of Heat and Mass Transfer and Its Applications in Power Technology [M ] . Beijing : China Electric Power Press , 2006 : 137 - 140 .

WANG P , CAO H , XIAO J . Structure Design of a Four‐Pillar Magnetically Integrated Fractional‐Turn Planar Transformer and its Loss Analysis [J ] . IEEJ Transactions on Electrical & Electronic Engineering , 2025 , 20 ( 2 ).

苏小平 , 陈伟根 , 胡启元 , 等 . 基于解析-数值技术的变压器绕组温度分布计算 [J ] . 高电压技术 , 2014 , 40 ( 10 ): 3164 - 3170 .

SU Xiaopin , CHEN Weigen , HU Qiyuan , et al . Calculation for Transformer Winding Temperature Distribution by Numerical Analytical Technology [J ] . High Voltage Engineering , 2014 , 40 ( 10 ): 3164 - 3170 .

郝钰 , 石华林 , 范瑞祥 , 等 . 基于动态热路模型的配电变压器过载工况下温升研究 [J ] . 变压器 , 2020 , 57 ( 12 ): 22 - 26 .

HAO Yu , SHI Hualin , FAN Ruixiang , et al . Study on Temperature Rise of Distribution Transformer Under Overload Condition Based on Dynamic Thermal Circuit Model [J ] . Transformer , 2020 , 57 ( 12 ): 22 - 26 .

万萌 , 应展烽 , 张旭东 , 等 . 功率器件集总参数热路模型及其参数提取研究 [J ] . 电工技术学报 , 2015 , 30 ( 21 ): 31 - 38 .

WAN Meng , YING Zhanfeng , ZHANG Xudong , et al . Research on the Lumped Parameter Thermal Circuit Model and the Parameter Extraction Method of Power Devices [J ] . Transactions of China Electrotechnical Society , 2015 , 30 ( 21 ): 31 - 38 .

TAGHIKHANI M A . Heat transfer modeling in a transformer using magneto-CFD analysis and GWO algorithm considering dynamic thermal model [J ] . Results in Engineering , 2024 , 23 : 000 .

JI N S , XU X , WANG H , et al . Thermal behavior calculation model of oil-immersed transformer winding based on thermoelectric analogy theory [J ] . Control and Instruments in Chemical Industry , 2019 .

TANG W , WU Q . Thermoelectric analogy thermal models of power transformers [J ] . Power Systems , 2011 : 55 - 71 .

MONFARED H J . Thermoelectric analogy thermal models of power transformers [J ] . 2016 .

KULKARNI S V , KHAPARDE S A . Transformer engineering: design, technology, and diagnostics [M ] . 2017 .

DING Y , ZHANG Q , GAO M , et al . Distributed thermal circuit model of oil-immersed distribution transformers [J ] . High Voltage Engineering , 2019 , 45 ( 3 ): 968 - 974 .

WANG F , ZHANG X , GAO , et al . Improved thermal circuit model of hot spot temperature in oil-immersed transformers based on heat distribution of winding [J ] . High Voltage Engineering , 2015 , 41 ( 3 ): 895 - 901 .

CHEN W , PENG C , YU Y . Power transformer top-oil temperature model based on thermal-electric analogy theory [J ] . European transactions on electrical power engineering , 2009 .

MIKHAK-BEYRANVAND M , FAIZ J , REZAEEALAM B . Thermal analysis of power transformer using an improved dynamic thermal equivalent circuit model [J ] . Electric Power Components and Systems , 2019 .

张旭辉 , 林海军 , 刘明珠 , 等 . 基于蚁群粒子群优化的卡尔曼滤波算法模型参数辨识 [J ] . 电力系统自动化 , 2014 , 38 ( 4 ): 44 - 50 .

ZHANG Xuhui , LIN Haijun , LIU Mingzhu , et al . Model Parameters Identification of UKF Algorithm Based on ACO-PSO [J ] . Automation of Electric Power Systems , 2014 , 38 ( 4 ): 44 - 50 .

王磊 , 李宏 , 武明珠 , 等 . 基于扩展卡尔曼滤波的永磁同步电动机参数辨识 [J ] . 微特电机 , 2012 , 40 ( 7 ): 19 - 22 .

WANG Lei , LI Hong , WU Mingzhu , et al . Parameters Identification of PMSM Based on Extended Kalman Filter [J ] . Small & Special Electrical Machines , 2012 , 40 ( 7 ): 19 - 22 .

田晓宇 , 李明干 , 刘沛 . 基于Kalman滤波的神经网络学习算法及其应用 [J ] . 计算机与数字工程 , 2005 , 33 ( 2 ): 4 .

TIAN Xiaoyu , LI Minggan , LIU Pei . Kalman Filter Learning Algorithm for Feedforward Neural Network and its Applicaion [J ] . Computer & Digital Engineering , 2005 , 33 ( 2 ): 4 .

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