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
Main Authors: Souza, Kleymilson N., Castro, Thiago N., Pereira, Thiago M., Pontes, Ricardo S. T., Braga, Arthur P. S.
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Core loss
Magnetic hysteresis
Neurons
Power transformers
Transformer cores
Online Access:Request full text
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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.
ISSN:0271-4302
2158-1525
DOI:10.1109/ISCAS.2011.5937763