Extração de harmônicos, inter e sub-harmônicos utilizando análise de componentes independentes

Detalhes bibliográficos
Ano de defesa: 2019
Autor(a) principal: Rufino Júnior, Carlos Antônio
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Lavras
Programa de Pós-graduação em Engenharia de Sistemas e Automação
UFLA
brasil
Departamento de Engenharia
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufla.br/jspui/handle/1/35022
Resumo: The increase in demand for electricity, mainly due to the appearance of new electronic equipment and the increase in the number of consumers, has motivated the search for clean and renewable energy sources and the emergence of the context of distributed generation. Distributed generation is characterized by small generation plants connected to the main electrical system. This new context has contributed to the increase of electric power quality problems, with emphasis on the increase of sources of harmonic, inter-harmonic and sub-harmonic components in the Electric Power System. Such components generate a number of problems, such as improper protection operation, measurement errors, line overheating and losses in transformers. In this way, the extraction of harmonic, inter-harmonic and sub-harmonic components of the electric system is of paramount importance. The present work proposes the implementation of the Filters-Analysis of Independent Components (FICA) method adapted to the problem of extraction of harmonics, sub-harmonics and inter-harmonics of the voltage signal and/or current of the electric power system. We evaluated 10 synthetic signals known in the current literature containing harmonics, inter-harmonics and sub-harmonics. In these signals were introduced disturbances such as sagging, oscillatory transients and noise. The results showed that the FICA - adapted method is able to extract the fundamental component and the harmonic, inter-harmonic and sub-harmonic components present in the voltage and/or processed current signal. As metrics, MSE, RRMSE, SD and RSD were used. The results show that the proposed method presents competitive results in view of several advantages over other methods in the literature, since it does not require the clustering step as in methods that use Single Channel Independent Component Analysis (SCICA), as well as method is able to extract components with low energy and components with low and high frequencies. In addition, the proposed method does not require parameters of the monitored electric signal, acts as an adaptive filter, does not suffer from fundamental frequency variations, and has the ability to extract interharmonics and subharmonics adjacent to the harmonic components. For future work it is expected to implement the proposed method online.