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Dynamic Loading of Substation Distribution Transformers: Detecting Unreliable Thermal Models and Improving the Accuracy of Predictions

Abstract t temperature (HST) and top-oil temperature (TOT) are reliable indicators of the insulation temperature. The objective of this project is to use thermal models to estimate the transformer's maximum dynamic loading capacity without violating the HST and TOT thermal limits set by the operator. In order to ensure the optimal loading, the temperature predictions of the thermal models need to be accurate. A number of transformer thermal models are available in the literature. In present practice, the IEEE Clause 7 model is used by the industry to make these predictions. However, a linear regression based thermal model has been observed to be more accurate than the IEEE model. These two models have been studied in this work.

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Created Date 2014
Contributor Rao, Shruti Dwarkanath (Author) / Tylavsky, Daniel J (Advisor) / Holbert, Keith (Committee member) / Karady, George (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Dynamic / Loading / Prediction / Thermal / Transformer
Type Masters Thesis
Extent 113 pages
Language English
Reuse Permissions All Rights Reserved
Note Masters Thesis Engineering 2014
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis