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Empirical Thermal Investigation of Oil–Immersed Distribution Transformer under Various Loading Conditions

Syed Ali Raza*, Ahsan Ullah, Shuang He, Yifeng Wang, Jiangtao Li

School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

* Corresponding Author:Syed Ali Raza. Email:

(This article belongs to this Special Issue: Recent Trends in Nanofluids: Modelling and Simulations)

Computer Modeling in Engineering & Sciences 2021, 129(2), 829-847.


The distribution transformer is the mainstay of the power system. Its internal temperature study is desirable for its safe operation in the power system. The purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading conditions. To achieve this goal, the temperature distribution in the oil, core, and windings are studied at each loading. An experimental study is performed with a 10/0.38 kV, 10 kVA oil–immersed transformer equipped with forty–two PT100 sensors (PTs) for temperature measurement installed inside during its manufacturing process. All possible locations for the hottest spot temperature (HST) are considered that made by finite element analysis (FEA) simulation and losses calculations. A resistive load is made to achieve 80% to 120% loading of the test transformer for this experiment. Working temperature is measured in each part of the transformer at all provided loading conditions. It is observed that temperature varies with loading throughout the transformer, and a detailed map of temperature is obtained in the whole test transformer. From these results, the HST stays in the critical section of the primary winding at all loading conditions. This work is helpful to understand the complete internal temperature layout and the location of the HST in distribution transformers.


Cite This Article

Raza, S. A., Ullah, A., He, S., Wang, Y., Li, J. (2021). Empirical Thermal Investigation of Oil–Immersed Distribution Transformer under Various Loading Conditions. CMES-Computer Modeling in Engineering & Sciences, 129(2), 829–847.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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