Oil exponent thermal modelling for traction transformer under multiple overloads
| Autor: | Tang Haolong, Yi Cui, Wang Jian, Lei Guo, Lujia Wang, Lijun Zhou |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Momentum (technical analysis)
business.industry 020209 energy Flow (psychology) Energy Engineering and Power Technology 02 engineering and technology Mechanics Finite element method Physics::Fluid Dynamics Energy conservation Petroleum industry Control and Systems Engineering Heat transfer 0202 electrical engineering electronic engineering information engineering Radiator (engine cooling) Exponent Electrical and Electronic Engineering business Mathematics |
| Zdroj: | IET Generation, Transmission & Distribution. 12:5982-5989 |
| ISSN: | 1751-8695 1751-8687 |
| DOI: | 10.1049/iet-gtd.2018.5084 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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