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Acceptability of Four Transformer Top-Oil Thermal Models-Part I: Defining Metrics
Eventually, the prediction of transformer thermal performance for dynamic loading will be made using models distilled from measured data, rather than models derived from transformer heat-run tests. Which model(s) will be used for this purpose remains unclear. In this paper, we introduce metrics for...
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Published in: | IEEE transactions on power delivery 2008-04, Vol.23 (2), p.860-865 |
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description | Eventually, the prediction of transformer thermal performance for dynamic loading will be made using models distilled from measured data, rather than models derived from transformer heat-run tests. Which model(s) will be used for this purpose remains unclear. In this paper, we introduce metrics for measuring the acceptability of transformer thermal models. For a model to be acceptable, it must have the qualities of adequacy, accuracy, and consistency. We assess model adequacy using the metrics: prediction R 2 and plot of residuals against fitted values. To assess model consistency, we use the variance inflation factor (which measures multicollinearity), condition number, eigenstructure, parameter sensitivity, and the standard deviation of model parameters and predicted maximum steady-state load (SSL max ). To assess model accuracy, we use the comparison of model parameters with nominal values and error duration curves. Other metrics of interest are also introduced. In a companion paper, these metrics are applied to the four models defined in this paper and a relative ranking of the acceptability of these models is presented. |
doi_str_mv | 10.1109/TPWRD.2007.905555 |
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Which model(s) will be used for this purpose remains unclear. In this paper, we introduce metrics for measuring the acceptability of transformer thermal models. For a model to be acceptable, it must have the qualities of adequacy, accuracy, and consistency. We assess model adequacy using the metrics: prediction R 2 and plot of residuals against fitted values. To assess model consistency, we use the variance inflation factor (which measures multicollinearity), condition number, eigenstructure, parameter sensitivity, and the standard deviation of model parameters and predicted maximum steady-state load (SSL max ). To assess model accuracy, we use the comparison of model parameters with nominal values and error duration curves. Other metrics of interest are also introduced. 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Electrical power engineering</subject><subject>Exact sciences and technology</subject><subject>Load modeling</subject><subject>Measurement standards</subject><subject>Performance evaluation</subject><subject>Predictive models</subject><subject>Standard deviation</subject><subject>Statistical distributions</subject><subject>Steady-state</subject><subject>Studies</subject><subject>Temperature</subject><subject>Testing</subject><subject>Thermal loading</subject><subject>Thermal resistance</subject><subject>top-oil temperature</subject><subject>transformer</subject><subject>transformer thermal modeling</subject><subject>Transformers and inductors</subject><issn>0885-8977</issn><issn>1937-4208</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><recordid>eNp9kU1P4zAQhi3EShR2fwDiEiEBp3THH4ltbgiWDwkEi4o4Wo4zBqM0KXZ66L9f0yIOHHYuHsvPvJ6Zl5B9ClNKQf-ePTw_XkwZgJxqqHJskQnVXJaCgdomE1CqKpWWcofspvQGAAI0TMjfM-dwMdomdGFcFYMvLodlLGbR9skPcY45HxblfeiK2SvGue2Ku6HFLpUPNo7FzWlxgT70oX8p7nCMwaWf5Ie3XcJfn-ceebr8Mzu_Lm_vr27Oz25Lx1U1lqyum0Z5hpVnFWrWWiaEVUK2jMm2YSi01IiQb1BxXTVSgHJtrWjjtVQt3yMnG91FHN6XmEYzD8lh19keh2UyGnhNudZ1Jo__S3IhaA0MMnj4DXzLy-jzFEbVHICCVBmiG8jFIaWI3iximNu4MhTMhxdm7YX58MJsvMg1R5_CNjnb-bxdF9JXYf5aCb1u4GDDBUT8ehaihkoB_wd2zpAt</recordid><startdate>20080401</startdate><enddate>20080401</enddate><creator>Jauregui-Rivera, L.</creator><creator>Tylavsky, D.J.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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subjects | ANSI C5791 Applied sciences Electrical engineering. Electrical power engineering Exact sciences and technology Load modeling Measurement standards Performance evaluation Predictive models Standard deviation Statistical distributions Steady-state Studies Temperature Testing Thermal loading Thermal resistance top-oil temperature transformer transformer thermal modeling Transformers and inductors |
title | Acceptability of Four Transformer Top-Oil Thermal Models-Part I: Defining Metrics |
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