Participatory Learning in Power Transformers Thermal Modeling

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.