METODOLOGIA PARA REDUÇÃO DE CUSTOS NA MANUTENÇÃO DOS COMUTADORES DE TAP SOB CARGA DOS TRANSFORMADORES DE POTÊNCIA DE EXTRA ALTA TENSÃO DA ELETRONORTE

Abstract

In this work a methodology for reduction of maintenance cost in the on-load tap changers (OLTC) of extra high voltage is proposed. The methodology is based on the use of Artificial Neural Networks (ANN) for the intelligent processing of input signals of the commutator. The neural nets adequately trained allow to create an information system and dedicated diagnosis of the OLTC. This system can interpret and diagnosis the components through the real time input signals in order to delay the power transformer maintenance intervals, foreseeing when the OLTC is going to maintenance have intervention based on its condition. It has been adopted a multiperceptron ANN architecture in which the input vector has 22 components and the output considers only one component with the status of the OLTC condition in function of its operation time. This output information is used to determine the periods of maintenance of the commutators. It is reported an application of the proposed system considering the on load tap changer of an autotransformer bank of 500/230/13.8 kV, 600MVA of Centrais Elétricas do Norte do Brasil S/A (ELETRONORTE). The results indicate the advantages of the maintenance based on the condition using ANN.