Methods to detect incorrect fan status for transformer thermal models

Shruti Rao; Daniel Tylavsky; Ken Alteneder; Kenneth E. Brown; Jason Gunawardena; Thomas Larose

doi:10.1109/NAPS.2014.6965406

Methods to detect incorrect fan status for transformer thermal models

Shruti Rao, Daniel Tylavsky, Ken Alteneder, Kenneth E. Brown, Jason Gunawardena, Thomas Larose

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

Abstract

Transformers are seldom loaded to their maximum capacity as per the existing industry practices. The ultimate goal of this research project is to develop a method for predicting the maximum dynamic loading capability without violating the thermal limits of the transformer's insulation. Dynamic loading must account for, at minimum, load magnitude and shape, the ambient temperature, the external cooling conditions and the thermal limits. This paper discusses methods of detecting irregularities in the cooling mode transitions for substation distribution transformers. The two HST and TOT models considered in this paper are the non-linear IEEE model and the model built using linear regression techniques.

Original language	English (US)
Title of host publication	2014 North American Power Symposium, NAPS 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479959044
DOIs	https://doi.org/10.1109/NAPS.2014.6965406
State	Published - Nov 21 2014
Event	2014 North American Power Symposium, NAPS 2014 - Pullman, United States Duration: Sep 7 2014 → Sep 9 2014

Publication series

Name	2014 North American Power Symposium, NAPS 2014

Other

Other	2014 North American Power Symposium, NAPS 2014
Country/Territory	United States
City	Pullman
Period	9/7/14 → 9/9/14

ASJC Scopus subject areas

Fuel Technology
Energy Engineering and Power Technology

Access to Document

10.1109/NAPS.2014.6965406

Cite this

Rao, S., Tylavsky, D., Alteneder, K., Brown, K. E., Gunawardena, J., & Larose, T. (2014). Methods to detect incorrect fan status for transformer thermal models. In 2014 North American Power Symposium, NAPS 2014 Article 6965406 (2014 North American Power Symposium, NAPS 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NAPS.2014.6965406

Methods to detect incorrect fan status for transformer thermal models. / Rao, Shruti; Tylavsky, Daniel; Alteneder, Ken et al.
2014 North American Power Symposium, NAPS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. 6965406 (2014 North American Power Symposium, NAPS 2014).

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

Rao, S, Tylavsky, D, Alteneder, K, Brown, KE, Gunawardena, J & Larose, T 2014, Methods to detect incorrect fan status for transformer thermal models. in 2014 North American Power Symposium, NAPS 2014., 6965406, 2014 North American Power Symposium, NAPS 2014, Institute of Electrical and Electronics Engineers Inc., 2014 North American Power Symposium, NAPS 2014, Pullman, United States, 9/7/14. https://doi.org/10.1109/NAPS.2014.6965406

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abstract = "Transformers are seldom loaded to their maximum capacity as per the existing industry practices. The ultimate goal of this research project is to develop a method for predicting the maximum dynamic loading capability without violating the thermal limits of the transformer's insulation. Dynamic loading must account for, at minimum, load magnitude and shape, the ambient temperature, the external cooling conditions and the thermal limits. This paper discusses methods of detecting irregularities in the cooling mode transitions for substation distribution transformers. The two HST and TOT models considered in this paper are the non-linear IEEE model and the model built using linear regression techniques.",

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AB - Transformers are seldom loaded to their maximum capacity as per the existing industry practices. The ultimate goal of this research project is to develop a method for predicting the maximum dynamic loading capability without violating the thermal limits of the transformer's insulation. Dynamic loading must account for, at minimum, load magnitude and shape, the ambient temperature, the external cooling conditions and the thermal limits. This paper discusses methods of detecting irregularities in the cooling mode transitions for substation distribution transformers. The two HST and TOT models considered in this paper are the non-linear IEEE model and the model built using linear regression techniques.

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Methods to detect incorrect fan status for transformer thermal models

Abstract

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