MARCELO ANTONIO ALVES LIMA - Academia.edu (original) (raw)
Uploads
Papers by MARCELO ANTONIO ALVES LIMA
Anais do Simpósio Brasileiro de Sistemas Elétricos 2020, 2020
Este artigo apresenta uma metodologia para a estimação de fontes de correntes harmônicas em siste... more Este artigo apresenta uma metodologia para a estimação de fontes de correntes harmônicas em sistemas elétricos de potência através do uso da análise complexa de componentes independentes (do inglês, Complex Independent Component Analysis (CICA)). A partir de medições fasoriais de tensão obtidas de uma rede elétrica, serão avaliados os perfis de variação rápida e lenta associados à curvas diárias de carga do sistema monitorado continuamente por PMUs (Phasor Measurement Units). Um algoritmo de filtragem baseado em média móvel é usado para desassociar estes dois perfis. A partir disso, a análise de componentes independentes fornece as estimações das fontes de corrente harmônicas no sistema, rastreando-as ao longo do tempo de observação. As simulações computacionais são conduzidas utilizando o sistema IEEE 14 barras a fim de validar a metodologia proposta.
This paper presents a methodology based on patterns recognition methods for the location of harmo... more This paper presents a methodology based on patterns recognition methods for the location of harmonic current sources. The circuits used were simulated using SIMULINK, the parameters used for the classification were generated based on higher order statistics and selected using Fisher’s descriptor. The classifiers used were Linear SVM (Support Vector Machine), nonlinear SVM and artificial neural network. The performances were compared with the purpose of demonstrating the effectiveness of the methodology developed. Resumo: Este trabalho apresenta uma metodologia baseada em métodos de reconhecimento de padrões para a localização de fontes de correntes harmônicas. Os circuitos utilizados foram simulados através do SIMULINK, os parâmetros utilizados para a classificação foram gerados baseado em estat́ısticas de ordem superior e selecionados utilizando o discriminante de Fisher. Os classificadores utilizados foram o SVM (Support Vector Machine) linear, SVM não linear e a rede neural artif...
This article presents a method for detecting novelties related to electrical disturbances in powe... more This article presents a method for detecting novelties related to electrical disturbances in power signals. The presented method uses a similarity metric as a detection parameter with an adaptive threshold that is adjusted to different waveforms. An adaptation to the detector to improve its performance is proposed. Simulation tests are performed, showing the effectiveness of the technique with different types of disturbances, and a comparison with another detection technique present in the literature is performed. Keywords— Novelty Detection, Power Quality, Similarity Metric. Resumo— O presente artigo apresenta um método de detecção de novidades relativas a distúrbios elétricos em sinais de potência. O método apresentado utiliza uma métrica de similaridade como parâmetro de detecção com um limiar adaptável que se ajusta a diferentes formas de onda. Uma adaptação ao detector é proposta, a fim de melhorar seu desempenho. São realizados testes de simulação, mostrando a eficácia do mesm...
Em muitas aplicações se faz necessário conhecer previamente o número exato de componentes senoida... more Em muitas aplicações se faz necessário conhecer previamente o número exato de componentes senoidais presentes em um sinal, como é o caso dos métodos paramétricos de alta resolução de frequência para estimação de parâmetros de componentes em sinais elétricos na presença de ruído. Este trabalho propõe a utilização de um método para estimação do número de componentes harmônicos e inter-harmônicos em sinais elétricos baseado em técnicas de subespaços e em teoria da informação. Trata-se de um método recursivo que se utiliza do rastreador de subespaços PASTd (Projection Approximation Subspace Tracking with deflation), que apresenta complexidade computacional baixa de ordem O(mr), onde m denota o tamanho do vetor de entrada e r a dimensão do subespaço de sinal. Além disso, o método utiliza um detector de ordem baseado nos critérios advindos da teoria da informação AIC (Akaike Information Criterion) e MDL (Minimum Description Length). Resultados de diversos testes de simulação serão gerados...
This paper exposes the hardware implementation of a real time dynamic resampling method, which co... more This paper exposes the hardware implementation of a real time dynamic resampling method, which contains a step for frequency estimation, an algorithm for obtaining waveform interpolation using Lagrange method applied to Farrow structure, and an algorithm to perform the Discrete Fourier Transform (DFT). The first parameter estimated by the algorithm from consecutive samples is the frequency, the result of which is used by the subsequent algorithm, which deals with the interpolation of the signal. Finally, the Sliding Window Discrete Fourier Transform (SWDFT) is applied to the interpolated signal with coherently cycle sample number adjustment. It also displays the results obtained in the implementation of the algorithm in a microcontroller, in which the algorithm was subjected to a permeated signal with harmonic composition and frequency variation. Resumo: Este artigo expõe a implementação em hardware de um método de reamostragem dinâmica em tempo real, o qual contém uma etapa para es...
International Journal of Electrical Power & Energy Systems, 2021
The power distribution network is susceptible to several Power Quality (PQ) disturbances. Among t... more The power distribution network is susceptible to several Power Quality (PQ) disturbances. Among those, the harmonic and interharmonic distortions should be highlighted due to their high proliferation. This work proposes the utilization of signal processing techniques to decompose the electrical voltage and/or current signals into its harmonic and interhamonic component waveforms through a Blind Source Separation (BSS) algorithm named Second Order Blind Identification (SOBI). This algorithm is normally applied to a multivariate data set, what implies in a necessity of multiple measurements in different points of the system that will be analyzed. However, Single-Channel Blind Source Separation (SCBSS) method will be proposed in this work to estimate the components via SOBI using only one measured signal point. The method works as a set of adaptive filters whose coefficients are blindly obtained via SOBI and is responsible for the components separation. An Exact Model Order (EMO) algorithm will be used to improve the performance of the SOBI algorithm in order to estimate the correct number of components to be separated. Also, the EMO will be helpful to reduce the computational complexity of the SOBI. The performance of the proposed SCBSS method will be compared to that of the SCICA (Single-Channel Independent Component Analysis) based on the well-known FastICA algorithm, which employs Higher Order Statistics (HOS). It will be shown that the proposed SCBSS overtakes the SCICA for harmonic and interharmonic decomposition in performance and in reduced computational complexity. Also, the proposed SCBSS method will be compared to EMO-ESPRIT algorithm, where will be shown that the SCBSS achieved better results in noisy and time-varying scenarios. Finally, the proposed SCBSS will be applied for the analysis of a voltage signal acquired from the simulation of a power system containing wind generation.
Electronics, 2019
Due to the highly increasing integration of renewable energy sources with the power grid and thei... more Due to the highly increasing integration of renewable energy sources with the power grid and their fluctuations, besides the recent growth of new power electronics equipment, the noise in power systems has become colored. The colored noise affects the methodologies for power quality parameters’ estimation, such as harmonic and interharmonic components. Estimation of signal parameters via rotational invariance techniques (ESPRIT) as a parametric technique with high resolution has proven its efficiency in the estimation of power signal components’ frequencies, amplitudes, and phases for quality analysis, under the assumption of white Gaussian noise. Since ESPRIT suffers from high computational effort, filter bank ESPRIT (FB-ESPRIT) was suggested for mitigation of the complexity. This manuscript suggests FB-ESPRIT as well for accurate and robust estimation of power signal components’ parameters in the presence of the colored noise. Even though the parametric techniques depend on the Ga...
Journal of Control, Automation and Electrical Systems, 2013
This paper proposes a method based on single channel independent component analysis for single an... more This paper proposes a method based on single channel independent component analysis for single and multiple power quality disturbance classification. The proposed method decouples the power system signal into its independent components, which are classified by specialized classifiers. The classifier outputs are combined by using a logic that gives the final classification. Five classes of single disturbances and twelve of multiple disturbances are considered and a classification efficiency above 97% is achieved for each event class. Both qualitative and quantitative analysis elucidate the efficiency of the proposed method. Results are obtained from both simulated and experimental signals.
Anais do Simpósio Brasileiro de Sistemas Elétricos 2020, 2020
Este artigo apresenta uma metodologia para a estimação de fontes de correntes harmônicas em siste... more Este artigo apresenta uma metodologia para a estimação de fontes de correntes harmônicas em sistemas elétricos de potência através do uso da análise complexa de componentes independentes (do inglês, Complex Independent Component Analysis (CICA)). A partir de medições fasoriais de tensão obtidas de uma rede elétrica, serão avaliados os perfis de variação rápida e lenta associados à curvas diárias de carga do sistema monitorado continuamente por PMUs (Phasor Measurement Units). Um algoritmo de filtragem baseado em média móvel é usado para desassociar estes dois perfis. A partir disso, a análise de componentes independentes fornece as estimações das fontes de corrente harmônicas no sistema, rastreando-as ao longo do tempo de observação. As simulações computacionais são conduzidas utilizando o sistema IEEE 14 barras a fim de validar a metodologia proposta.
This paper presents a methodology based on patterns recognition methods for the location of harmo... more This paper presents a methodology based on patterns recognition methods for the location of harmonic current sources. The circuits used were simulated using SIMULINK, the parameters used for the classification were generated based on higher order statistics and selected using Fisher’s descriptor. The classifiers used were Linear SVM (Support Vector Machine), nonlinear SVM and artificial neural network. The performances were compared with the purpose of demonstrating the effectiveness of the methodology developed. Resumo: Este trabalho apresenta uma metodologia baseada em métodos de reconhecimento de padrões para a localização de fontes de correntes harmônicas. Os circuitos utilizados foram simulados através do SIMULINK, os parâmetros utilizados para a classificação foram gerados baseado em estat́ısticas de ordem superior e selecionados utilizando o discriminante de Fisher. Os classificadores utilizados foram o SVM (Support Vector Machine) linear, SVM não linear e a rede neural artif...
This article presents a method for detecting novelties related to electrical disturbances in powe... more This article presents a method for detecting novelties related to electrical disturbances in power signals. The presented method uses a similarity metric as a detection parameter with an adaptive threshold that is adjusted to different waveforms. An adaptation to the detector to improve its performance is proposed. Simulation tests are performed, showing the effectiveness of the technique with different types of disturbances, and a comparison with another detection technique present in the literature is performed. Keywords— Novelty Detection, Power Quality, Similarity Metric. Resumo— O presente artigo apresenta um método de detecção de novidades relativas a distúrbios elétricos em sinais de potência. O método apresentado utiliza uma métrica de similaridade como parâmetro de detecção com um limiar adaptável que se ajusta a diferentes formas de onda. Uma adaptação ao detector é proposta, a fim de melhorar seu desempenho. São realizados testes de simulação, mostrando a eficácia do mesm...
Em muitas aplicações se faz necessário conhecer previamente o número exato de componentes senoida... more Em muitas aplicações se faz necessário conhecer previamente o número exato de componentes senoidais presentes em um sinal, como é o caso dos métodos paramétricos de alta resolução de frequência para estimação de parâmetros de componentes em sinais elétricos na presença de ruído. Este trabalho propõe a utilização de um método para estimação do número de componentes harmônicos e inter-harmônicos em sinais elétricos baseado em técnicas de subespaços e em teoria da informação. Trata-se de um método recursivo que se utiliza do rastreador de subespaços PASTd (Projection Approximation Subspace Tracking with deflation), que apresenta complexidade computacional baixa de ordem O(mr), onde m denota o tamanho do vetor de entrada e r a dimensão do subespaço de sinal. Além disso, o método utiliza um detector de ordem baseado nos critérios advindos da teoria da informação AIC (Akaike Information Criterion) e MDL (Minimum Description Length). Resultados de diversos testes de simulação serão gerados...
This paper exposes the hardware implementation of a real time dynamic resampling method, which co... more This paper exposes the hardware implementation of a real time dynamic resampling method, which contains a step for frequency estimation, an algorithm for obtaining waveform interpolation using Lagrange method applied to Farrow structure, and an algorithm to perform the Discrete Fourier Transform (DFT). The first parameter estimated by the algorithm from consecutive samples is the frequency, the result of which is used by the subsequent algorithm, which deals with the interpolation of the signal. Finally, the Sliding Window Discrete Fourier Transform (SWDFT) is applied to the interpolated signal with coherently cycle sample number adjustment. It also displays the results obtained in the implementation of the algorithm in a microcontroller, in which the algorithm was subjected to a permeated signal with harmonic composition and frequency variation. Resumo: Este artigo expõe a implementação em hardware de um método de reamostragem dinâmica em tempo real, o qual contém uma etapa para es...
International Journal of Electrical Power & Energy Systems, 2021
The power distribution network is susceptible to several Power Quality (PQ) disturbances. Among t... more The power distribution network is susceptible to several Power Quality (PQ) disturbances. Among those, the harmonic and interharmonic distortions should be highlighted due to their high proliferation. This work proposes the utilization of signal processing techniques to decompose the electrical voltage and/or current signals into its harmonic and interhamonic component waveforms through a Blind Source Separation (BSS) algorithm named Second Order Blind Identification (SOBI). This algorithm is normally applied to a multivariate data set, what implies in a necessity of multiple measurements in different points of the system that will be analyzed. However, Single-Channel Blind Source Separation (SCBSS) method will be proposed in this work to estimate the components via SOBI using only one measured signal point. The method works as a set of adaptive filters whose coefficients are blindly obtained via SOBI and is responsible for the components separation. An Exact Model Order (EMO) algorithm will be used to improve the performance of the SOBI algorithm in order to estimate the correct number of components to be separated. Also, the EMO will be helpful to reduce the computational complexity of the SOBI. The performance of the proposed SCBSS method will be compared to that of the SCICA (Single-Channel Independent Component Analysis) based on the well-known FastICA algorithm, which employs Higher Order Statistics (HOS). It will be shown that the proposed SCBSS overtakes the SCICA for harmonic and interharmonic decomposition in performance and in reduced computational complexity. Also, the proposed SCBSS method will be compared to EMO-ESPRIT algorithm, where will be shown that the SCBSS achieved better results in noisy and time-varying scenarios. Finally, the proposed SCBSS will be applied for the analysis of a voltage signal acquired from the simulation of a power system containing wind generation.
Electronics, 2019
Due to the highly increasing integration of renewable energy sources with the power grid and thei... more Due to the highly increasing integration of renewable energy sources with the power grid and their fluctuations, besides the recent growth of new power electronics equipment, the noise in power systems has become colored. The colored noise affects the methodologies for power quality parameters’ estimation, such as harmonic and interharmonic components. Estimation of signal parameters via rotational invariance techniques (ESPRIT) as a parametric technique with high resolution has proven its efficiency in the estimation of power signal components’ frequencies, amplitudes, and phases for quality analysis, under the assumption of white Gaussian noise. Since ESPRIT suffers from high computational effort, filter bank ESPRIT (FB-ESPRIT) was suggested for mitigation of the complexity. This manuscript suggests FB-ESPRIT as well for accurate and robust estimation of power signal components’ parameters in the presence of the colored noise. Even though the parametric techniques depend on the Ga...
Journal of Control, Automation and Electrical Systems, 2013
This paper proposes a method based on single channel independent component analysis for single an... more This paper proposes a method based on single channel independent component analysis for single and multiple power quality disturbance classification. The proposed method decouples the power system signal into its independent components, which are classified by specialized classifiers. The classifier outputs are combined by using a logic that gives the final classification. Five classes of single disturbances and twelve of multiple disturbances are considered and a classification efficiency above 97% is achieved for each event class. Both qualitative and quantitative analysis elucidate the efficiency of the proposed method. Results are obtained from both simulated and experimental signals.