Improving Reliability Assessment of Transformer Thermal Top-Oil Model Parameters Estimated From Measured Data

被引：14

作者：

Jauregui-Rivera, Lida ^{[1
]}

Mao, Xiaolin ^{[2
]}

Tylavsky, Daniel J. ^{[2
]}

机构：

[1] Arizona Publ Serv, Phoenix, AZ 85004 USA

[2] Arizona State Univ, Tempe, AZ 85287 USA

来源：

IEEE TRANSACTIONS ON POWER DELIVERY | 2009年 / 24卷 / 01期

关键词：

Bootstrapping; confidence intervals (CIs); confidence levels (CLs); least squares regression; parameter estimation; top-oil temperature; transformer thermal modeling; FUNDAMENTAL APPROACH;

D O I：

10.1109/TPWRD.2008.2005686

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a methodology for assessing the reliability of thermal-model parameters for transformers estimated from measured data. The methodology uses statistical bootstrapping to calculate confidence levels (CL) and confidence intervals (0). Bootstrapping allows us to make a small dataset look statistically larger, which allows a precise estimate of the transformer thermal model's reliability. The proposed methodology is tested on a 167-MVA oil-forced air-forced transformer. The CIs are evaluated with and without bootstrapping and the reliability indices are compared. The results show that the CI and CL values with bootstrapping are more consistently reproducible than the ones derived without bootstrapping.

引用

页码：169 / 176

页数：8

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