Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/33624
metadata.artigo.dc.title: Voltage sag and swell detection and segmentation based on independent component analysis
metadata.artigo.dc.creator: Nagata, Erick A.
Ferreira, Danton D.
Duque, Carlos A.
Cequeira, Augusto S.
metadata.artigo.dc.subject: Power quality
Voltage sag detection
Voltage sag segmentation
Independent component analysis
metadata.artigo.dc.publisher: Elsevier
metadata.artigo.dc.date.issued: Feb-2018
metadata.artigo.dc.identifier.citation: NAGATA, E. A. et al. Voltage sag and swell detection and segmentation based on independent component analysis. Electric Power Systems Research, [S.l.], v. 155, p. 274-280, Feb. 2018.
metadata.artigo.dc.description.abstract: In this paper, a new method for voltage sag and swell detection and segmentation, based on Independent Component Analysis, is presented. The proposed method uses single channel ICA (SCICA) to blindly design suitable filters for sag and swell detection and segmentation, even in the presence of power quality disturbances such as sinusoidal voltage fluctuation, fundamental frequency variations, harmonics and phase-angle-jump. The performance of the proposed method was evaluated for both synthetic and real signals, in which the beginning and ending times of sags and swells were accurately detected. Moreover, the results were compared with a Wavelet-based method, showing that the performance of the proposed ICA-based method was better than the Wavelet one. The proposed method also showed to be robust to noise and frequency variations.
metadata.artigo.dc.identifier.uri: https://www.sciencedirect.com/science/article/pii/S0378779617304352#fig0010
http://repositorio.ufla.br/jspui/handle/1/33624
metadata.artigo.dc.language: en_US
Appears in Collections:DAT - Artigos publicados em periódicos

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