Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/42428
metadata.artigo.dc.title: Compression method of power quality disturbances based on independent component analysis and fast Fourier transform
metadata.artigo.dc.creator: Pinto, Larissa S.
Assunção, Mateus V.
Ribeiro, David A.
Ferreira, Danton Diego
Huallpa, Belisário Nina
Silva, Leandro Rodrigues Manso
Duque, Carlos Augusto
metadata.artigo.dc.subject: Signal compression
Smart grids
Independent component analysis
Power quality
Compressão de sinais
Rede elétrica inteligente
Análise de componentes independentes
metadata.artigo.dc.publisher: Elsevier
metadata.artigo.dc.date.issued: Oct-2020
metadata.artigo.dc.identifier.citation: PINTO, L. S. et al. Compression method of power quality disturbances based on independent component analysis and fast Fourier transform. Electric Power Systems Research, [S. I.], v. 187, Oct. 2020. DOI: https://doi.org/10.1016/j.epsr.2020.106428.
metadata.artigo.dc.description.abstract: In power quality monitoring systems, a large volume of data is generated. A compression method should be used to perform the storage of data more efficiently. The present study proposes a compression method of power quality disturbances based on independent component analysis, Fast Fourier Transform and an adaptive threshold obtained using mathematical morphology. The independent component analysis algorithm returns three statistically independent components among themselves. Considering the noise and disturbances are statistically independent of the fundamental component, the independent component analysis algorithm isolates the noise and disturbances in the third component, where a threshold is applied, while the first and second components are presented to the Fast Fourier Transform in order to characterize the fundamental component. The results were compared with a Wavelet-based method in which the proposed method achieved compression rates slightly higher than the Wavelet-based method.
metadata.artigo.dc.identifier.uri: https://doi.org/10.1016/j.epsr.2020.106428
http://repositorio.ufla.br/jspui/handle/1/42428
metadata.artigo.dc.language: en
Appears in Collections:DAT - Artigos publicados em periódicos
DEG - Artigos publicados em periódicos

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