Paper
27 October 2023 Calculation model of hot-spot temperature of transformer winding based on top-oil temperature
Ming Dong, Wenjun Liu, Yue Chen, Kun Li, Yingan Zhi, Likun Meng
Author Affiliations +
Proceedings Volume 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023); 1292225 (2023) https://doi.org/10.1117/12.3009424
Event: The Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 2023, Xiamen, China
Abstract
Oil-immersed type transformer is an essential part of electric power system, and the hot-spot temperature of the winding is closely related to the oil temperature at the top of the transformer. In this paper, modeling of the thermal circuit based on the distribution of the top oil temperature of the double-wound transformer. On the basis of the consideration of nonlinear characteristics of thermal resistance of insulating oil, we also considered the influence of oil stickiness and the thermal capacitance of transformer components (iron core, insulating oil, windings) with temperature changes, and introduced the cooling ways and winding loss correction factors in the model. The Runge-Kutta method is selected to resolve the model parameters, which further simplified the calculation process. Above all, the improved model of hot- spot temperature of transformer winding is proposed. Contrast with testing transformer measured data in laboratory and calculation result of traditional hot spot analogy method, the model shows good consistency in the light load (around 20% and 40%), which can well describe the transient temperature change and propose a new method to calculate the hot- spot temperature of transformer winding.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Ming Dong, Wenjun Liu, Yue Chen, Kun Li, Yingan Zhi, and Likun Meng "Calculation model of hot-spot temperature of transformer winding based on top-oil temperature", Proc. SPIE 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 1292225 (27 October 2023); https://doi.org/10.1117/12.3009424
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KEYWORDS
Transformers

Temperature metrology

Resistance

Thermal modeling

Iron

Capacitance

Data modeling

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