Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 25, Issue 5, Pages 980-988Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2011.12.007
Keywords
Power transformers; Thermal modeling; Evolving fuzzy systems
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Funding
- Brazilian National Research Council, CNPq [141323/2009-4, 309666/2007-4]
- FAPEMIG, the Research Foundation of the State of Minas Gerais [PPM-00252-09]
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Thermal models for distribution transformers with core immersed in oil are of utmost importance for transformers lifetime study. The hot spot temperature determines the degradation speed of the insulating paper. High temperatures cause loss of mechanical stiffness, generating failures. Since the paper is the most fragile component of the transformer, its degradation determines the lifetime limits. Thus, good thermal models are needed to generate reliable data for lifetime forecasting methodologies. It is also desired that thermal models are able to adapt to cope with changes in the transformer behavior due to structural changes, maintenance and so on. In this work we apply an evolving fuzzy model to build adaptive thermal models of distribution transformers. The model used is able to adapt its parameters and also its structure based on a stream of data. The proposed model is evaluated using actual data from an experimental transformer. The results suggest that evolving fuzzy models are a promising approach for adaptive thermal modeling of distribution transformers. (C) 2012 Elsevier Ltd. All rights reserved.
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