Reliability assessment of transformer thermal model parameters estimated from measured data

L. Jauregui - Rivera; D. J. Tylavsky

doi:10.1109/NAPS.2005.1560501

Reliability assessment of transformer thermal model parameters estimated from measured data

L. Jauregui - Rivera, D. J. Tylavsky

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

This paper presents a methodology to assess the reliability of substation distribution transformer thermal model parameters estimated from measured data. The methodology uses statistical bootstrapping to assign a measure of reliability to the estimated parameters using confidence levels (CL) and confidence intervals (CI). The bootstrapping technique, which is used to make a small data sample look statistically large, allows a precise estimate of transformer reliability. The proposed methodology is tested on a 28 MVA transformer for which different data sets are available. The CI's are evaluated for both cases: with and without bootstrapping and the reliability indices compared. The results show that the CI values with bootstrapping are more consistently reproducible than the ones derived without bootstrapping.

Original language	English (US)
Title of host publication	Proceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006
Pages	52-58
Number of pages	7
DOIs	https://doi.org/10.1109/NAPS.2005.1560501
State	Published - Dec 1 2005
Externally published	Yes
Event	37th Annual North American Power Symposium, 2005 - Ames, IA, United States Duration: Oct 23 2005 → Oct 25 2005

Publication series

Name	Proceedings of the 37th Annual North American Power Symposium, 2005
Volume	2005

Other

Other	37th Annual North American Power Symposium, 2005
Country/Territory	United States
City	Ames, IA
Period	10/23/05 → 10/25/05

Keywords

Bootstrapping
Confidence intervals
Confidence levels
Hot-spot temperature
Least squares
Parameter estimation
Top-oil temperature
Transformer thermal modeling

ASJC Scopus subject areas

General Engineering

Access to Document

10.1109/NAPS.2005.1560501

Cite this

Jauregui - Rivera, L., & Tylavsky, D. J. (2005). Reliability assessment of transformer thermal model parameters estimated from measured data. In Proceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006 (pp. 52-58). Article 1560501 (Proceedings of the 37th Annual North American Power Symposium, 2005; Vol. 2005). https://doi.org/10.1109/NAPS.2005.1560501

Reliability assessment of transformer thermal model parameters estimated from measured data. / Jauregui - Rivera, L.; Tylavsky, D. J.
Proceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006. 2005. p. 52-58 1560501 (Proceedings of the 37th Annual North American Power Symposium, 2005; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Jauregui - Rivera, L & Tylavsky, DJ 2005, Reliability assessment of transformer thermal model parameters estimated from measured data. in Proceedings - Thirteenth International Symposium on Temporal Representation and Reasoning, TIME 2006., 1560501, Proceedings of the 37th Annual North American Power Symposium, 2005, vol. 2005, pp. 52-58, 37th Annual North American Power Symposium, 2005, Ames, IA, United States, 10/23/05. https://doi.org/10.1109/NAPS.2005.1560501

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title = "Reliability assessment of transformer thermal model parameters estimated from measured data",

abstract = "This paper presents a methodology to assess the reliability of substation distribution transformer thermal model parameters estimated from measured data. The methodology uses statistical bootstrapping to assign a measure of reliability to the estimated parameters using confidence levels (CL) and confidence intervals (CI). The bootstrapping technique, which is used to make a small data sample look statistically large, allows a precise estimate of transformer reliability. The proposed methodology is tested on a 28 MVA transformer for which different data sets are available. The CI's are evaluated for both cases: with and without bootstrapping and the reliability indices compared. The results show that the CI values with bootstrapping are more consistently reproducible than the ones derived without bootstrapping.",

keywords = "Bootstrapping, Confidence intervals, Confidence levels, Hot-spot temperature, Least squares, Parameter estimation, Top-oil temperature, Transformer thermal modeling",

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KW - Confidence intervals

KW - Confidence levels

KW - Hot-spot temperature

KW - Least squares

KW - Parameter estimation

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Reliability assessment of transformer thermal model parameters estimated from measured data

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Keywords

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