Transformer Top-Oil Temperature Modeling and Simulation

被引：0

作者：

Assuncao, T. C. B. N. ^{[1
]}

Silvino, J. L. ^{[2
]}

Resende, P. ^{[2
]}

机构：

[1] Univ Fed Sao Joao del Rei, Dept Elect Engn, Sao Joao Del Rei, MG, Brazil

[2] Univ Fed Minas Gerais, Dept Elect Engn, Belo Horizonte, MG, Brazil

来源：

PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 15 | 2006年 / 15卷

关键词：

Artificial Neural Networks; Hot-spot Temperature; Least Squares Support Vector; Top-oil Temperature;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The winding hot-spot temperature is one of the most critical parameters that affect the useful life of the power transformers. The winding hot-spot temperature can be calculated as function of the top-oil temperature that can estimated by using the ambient temperature and transformer loading measured data. This paper proposes the estimation of the top-oil temperature by using a method based on Least Squares Support Vector Machines approach. The estimated top-oil temperature is compared with measured data of a power transformer in operation. The results are also compared with methods based on the IEEE Standard C57.91-1995/2000 and Artificial Neural Networks. It is shown that the Least Squares Support Vector Machines approach presents better performance than the methods based in the IEEE Standard C57.91-1995/2000 and artificial neural networks.

引用

页码：240 / +

页数：2

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