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Transformer thermal modeling: improving reliability using data quality control

Eventually, all large transformers will be dynamically loaded using models updated regularly from field-measured data. Models obtained from measured data give more accurate results than models based on transformer heat-run tests and can be easily generated using data already routinely monitored. The...

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Published in:	IEEE transactions on power delivery 2006-07, Vol.21 (3), p.1357-1366
Main Authors:	Tylavsky, D.J., Xiaolin Mao, McCulla, G.A.
Format:	Article
Language:	English
Subjects:	ANSI C57.91 Applied sciences Cooling Electrical engineering. Electrical power engineering Error correction Errors Exact sciences and technology Heat transfer Load modeling Mathematical models Monitoring Nonlinearity Predictive models Quality control Screening Temperature measurement Testing Thermal loading top-oil temperature transformer transformer thermal modeling Transformers Transformers and inductors
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container_title	IEEE transactions on power delivery
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creator	Tylavsky, D.J. Xiaolin Mao McCulla, G.A.
description	Eventually, all large transformers will be dynamically loaded using models updated regularly from field-measured data. Models obtained from measured data give more accurate results than models based on transformer heat-run tests and can be easily generated using data already routinely monitored. The only significant challenge to use these models is to assess their reliability and improve their reliability as much as possible. In this work, we use data-quality control and data-set screening to show that model reliability can be increased by about 50% while decreasing model prediction error. These results are obtained for a linear model. We expect similar results for the nonlinear models currently being explored.
doi_str_mv	10.1109/TPWRD.2005.864039
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subjects	ANSI C57.91 Applied sciences Cooling Electrical engineering. Electrical power engineering Error correction Errors Exact sciences and technology Heat transfer Load modeling Mathematical models Monitoring Nonlinearity Predictive models Quality control Screening Temperature measurement Testing Thermal loading top-oil temperature transformer transformer thermal modeling Transformers Transformers and inductors
title	Transformer thermal modeling: improving reliability using data quality control
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