Oil exponent thermal modelling for traction transformer under multiple overloads
Article
Article Title | Oil exponent thermal modelling for traction transformer under multiple overloads |
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ERA Journal ID | 4574 |
Article Category | Article |
Authors | Zhou, Lijun (Author), Wang, Lujia (Author), Tang, Haolong (Author), Wang, Jian (Author), Guo, Lei (Author) and Cui, Yi (Author) |
Journal Title | IET Generation, Transmission and Distribution |
Journal Citation | 12 (22), pp. 5982-5989 |
Number of Pages | 8 |
Year | 2018 |
Place of Publication | United Kingdom |
ISSN | 1350-2360 |
1751-8687 | |
1751-8695 | |
Digital Object Identifier (DOI) | https://doi.org/10.1049/iet-gtd.2018.5084 |
Web Address (URL) | https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/iet-gtd.2018.5084 |
Abstract | To quantify the non-linear variation of top-oil temperature with load current, and further investigate the key parameters in the thermal model, a model for calculating the oil exponent is proposed in this study. First, a global oil momentum model was established based on the fluid resistance characteristic. Then, based on the heat transfer coupling relationship between the winding, the oil flow, and the radiator (outside air), a set of control equations describing the oil temperature and the oil flow rate was established by using energy conservation. Simultaneously, the top-oil temperature was recorded from a field traction transformer to verify the physical part of the proposed model. The regression model parameters were identified with the ordinary least-square estimation so the oil exponent can be calculated naturally. The calculated oil exponent of the traction transformer at a wide range of load was 0.7308, so the accuracy was improved by 9.47% compared with the IEEE/IEC recommended value. Newly updated oil exponent was also verified through a dynamic overload heat run test. It is expected that the proposed oil exponent model can help in estimating top-oil temperature with more convenience and accuracy, especially in frequent overload conditions. |
Keywords | Coupling relationships; Non-linear variation; Ordinary least squares; Overload condition; Recommended values; Thermal modelling; Top oil temperature; Traction transformer |
ANZSRC Field of Research 2020 | 400803. Electrical energy generation (incl. renewables, excl. photovoltaics) |
Byline Affiliations | Southwest Jiaotong University, China |
University of Tennessee, United States | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q7w26/oil-exponent-thermal-modelling-for-traction-transformer-under-multiple-overloads
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