New phenemenon on power transformers and fault identification using artificial neural networks

Şengül M., Öztürk S., Çetinkaya H. B., Erfidan T.

16th International Conference on Artificial Neural Networks, ICANN 2006, Athens, Greece, 10 - 14 September 2006, vol.4132 LNCS - II, pp.767-776, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 4132 LNCS - II
  • Doi Number: 10.1007/11840930_80
  • City: Athens
  • Country: Greece
  • Page Numbers: pp.767-776
  • Kocaeli University Affiliated: Yes

Abstract

In this paper voltage recovery after voltage dip that cause magnetizing inrush current which is a new phenomenon in power transformers are discussed and a new technique is proposed to distinquish internal fault conditions from no-fault conditions that is also containing these new phenomenons. The proposed differential algorithm is based on Artificial Neural Network (ANN). The training and testing data sets are obtained using SIMPOW-STRI power system simulation program and laboratory transformer. A novel neural network is designed and trained using back-propagation algorithm. It is seen that the proposed network is well trained and able to discriminate no-fault examples from fault examples with high accuracy. © Springer-Verlag Berlin Heidelberg 2006.