Otro
A computational tool to assist the analysis of the transformer behavior related to lightning
Registro en:
International Journal of Electrical Power & Energy Systems. Oxford: Elsevier B.V., v. 33, n. 3, p. 556-561, 2011.
0142-0615
10.1016/j.ijepes.2010.11.009
WOS:000288842800025
Autor
de Souza, Andre N.
Zago, Maria G.
Saavedra, Osvaldo R.
Oba Ramos, Caio C.
Ferraz, Kleber
Resumen
This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. (C) 2011 Elsevier Ltd. All rights reserved.