Publicação: Detection and Classification of Voltage Disturbances in Electrical Power Systems Using a Modified Euclidean ARTMAP Neural Network with Continuous Training
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Data
2015-11-26
Orientador
Coorientador
Pós-graduação
Curso de graduação
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Título de Volume
Editor
Taylor & Francis Inc
Tipo
Artigo
Direito de acesso
Acesso aberto
Resumo
This article presents a method to detect and classify voltage disturbances in electric power distribution systems using a modified Euclidean ARTMAP neural network with continuous training. This decision-making tool accelerates the procedures to restore the normal operation conditions providing security, reliability, and profits to utilities. Furthermore, it allows the diagnosis system to adapt to changes from the constant evolution of the electric system. The voltage signals features or signatures are extracted using discrete wavelet transform, multiresolution analysis, and the energy concept. Results show that the proposed methodology is robust and efficient, providing a fast diagnosis process. The data set used to validate the proposal is obtained by simulations in a real distribution system using ATP software.
Descrição
Idioma
Inglês
Como citar
Electric Power Components And Systems. Philadelphia: Taylor & Francis Inc, v. 43, n. 19, p. 2178-2188, 2015.
