Title :
Participatory Learning in Power Transformers Thermal Modeling
Author :
Hell, Michel ; Costa, Pyramo, Jr. ; Gomide, Fernando
Author_Institution :
Dept. of Comput. Eng. & Autom. (DCA), State Univ. of Campinas (UNICAMP), Campinas
Abstract :
In this paper, we introduce a new approach based on the participatory learning paradigm to train a class of hybrid neurofuzzy networks whose aim is to model the thermal behavior of power transformers. The participatory learning paradigm is a training procedure that tends to emulate the human learning mechanism. An acceptance mechanism determines which observation is used for learning based upon their compatibility with the current beliefs. The proposed model is compared with actual data obtained from an experimental power transformer equipped with fiber-optic probes. Comparisons with alternative approaches suggested in the literature are included to show the effectiveness of participatory learning to model the thermal behavior of power transformers.
Keywords :
fuzzy neural nets; learning (artificial intelligence); power engineering computing; power transformers; hybrid neurofuzzy networks; participatory learning paradigm; power transformers; thermal modeling; Nonlinear modeling; participatory learning; power transformers; thermal modeling;
Journal_Title :
Power Delivery, IEEE Transactions on
DOI :
10.1109/TPWRD.2008.923994