Prediction of core losses on a three-phase transformer using neural networks

This work is a study of intelligent tools for forecasting losses in the transformer core, comparing with the traditionally accepted model. The uses of Artificial Neural Networks (ANN) search a best estimator of losses in the transformer core. Two models of ANN were proposed: Multi-Layer Percepton (M...

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Bibliographic Details
Published in2011 IEEE International Symposium of Circuits and Systems (ISCAS) pp. 1105 - 1108
Main Authors Souza, Kleymilson N., Castro, Thiago N., Pereira, Thiago M., Pontes, Ricardo S. T., Braga, Arthur P. S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2011
Subjects
Artificial neural networks
Core loss
Magnetic hysteresis
Neurons
Power transformers
Transformer cores
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Summary:This work is a study of intelligent tools for forecasting losses in the transformer core, comparing with the traditionally accepted model. The uses of Artificial Neural Networks (ANN) search a best estimator of losses in the transformer core. Two models of ANN were proposed: Multi-Layer Percepton (MLP) and Neo-Fuzzy Neuron (NFN). After an analysis of the model they were evaluated and it was concluded that the MLP model for this application had the best performance.
ISBN:1424494737
9781424494736
ISSN:0271-4302
2158-1525
DOI:10.1109/ISCAS.2011.5937763