Proposta de Algoritmos Inteligentes para Localizar Faltas e Monitorar a Qualidade da Energia em Redes de Distribuição de Energia Elétrica
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Data
2013-04-25
Autores
Bíscaro, André do Amaral Penteado [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
Neste trabalho apresenta-se uma metodologia para a localização e diagnóstico automático de faltas em alimentadores de distribuição de energia elétrica através do uso combinado de técnicas de análise de redes, processamento de sinais e sistemas inteligentes. Foram desenvolvidos algoritmos capazes de detectar, classificar e localizar no tempo e espaço, os eventos de qualidade de energia. O procedimento contínuo de detecção de distúrbios é realizado através de análises estatísticas diretas e multinível dos sinais de correntes no domínio wavelet, registrados na subestação. As principais características, ou índices comportamentais, dos sinais das correntes e tensões são extraídas empregando-se a transformada wavelet discreta, a análise multirresolução e o conceito de energia do sinal. Estes índices correspondem aos vetores de entrada de um conjunto de redes neurais ARTMAP Fuzzy independentes, que tem por finalidade estimar o tipo de falta e quais eventos de qualidade de energia estão presentes no sinal amostrado. Os padrões de entrada destas redes são compostos pela energia dos coeficientes dos quatro primeiros níveis de detalhes e aproximações dos sinais de tensão e corrente e, na saída dessas redes, como resposta, tem-se o código do tipo de distúrbio e as fases envolvidas no problema. A localização do distúrbio é realizada após o processo de classificação, sendo que a técnica de localização de faltas proposta aplica-se a alimentadores trifásicos radiais ou fracamente malhados, com cargas desequilibradas, ramais laterais trifásicos, bifásicos ou monofásicos e que possam apresentar geração distribuída. O sistema de diagnóstico e localização de faltas proposto neste trabalho é capaz de auxiliar as concessionárias de energia em sua rotina de trabalho, fornecendo informações importantes para...
This work presents a methodology for automatic diagnosis and fault location on electric power distribution systems through the combined use of modern techniques of network analysis, signal processing and, intelligent systems. Some algorithms were developed aiming to detect, classify and locate in time and space the power quality disturbances. The continuous process of detecting these disturbances is accomplished through statistical analysis and direct current multilevel signal analysis in wavelet domain, recorded in the substation. The main characteristics, or behavioral indices, of the current and voltage signals are extracted employing the discrete wavelet transform, multiresolution analysis and the concept of signal energy. These indexes correspond to the input vectors of a number of independent Fuzzy ARTMAP neural networks, which aim to estimate the fault type and the power quality events that are present in the sampled signal. The input patterns of these networks are composed by energy coefficients of the first four levels of details and approximations of current and voltage signals and, the output network presents the disorder type code and the phases involved in the problem. The fault location is performed after the classification process, and the proposed technique applies to three-phase radial or weakly meshed feeders with unbalanced loads, lateral extensions triphasic, biphasic or, monophasic and presenting distributed generation. The system diagnosis and fault location proposed in this paper are able to assist the utilities in their daily works, providing important information for the operation and maintenance of power distribution systems, minimizing the repairing time and, consequently, obtaining less financial losses due to rapid fault diagnosis and restoration of the normal system operation. A real life three-phase... (Complete abstract click electronic access below)
This work presents a methodology for automatic diagnosis and fault location on electric power distribution systems through the combined use of modern techniques of network analysis, signal processing and, intelligent systems. Some algorithms were developed aiming to detect, classify and locate in time and space the power quality disturbances. The continuous process of detecting these disturbances is accomplished through statistical analysis and direct current multilevel signal analysis in wavelet domain, recorded in the substation. The main characteristics, or behavioral indices, of the current and voltage signals are extracted employing the discrete wavelet transform, multiresolution analysis and the concept of signal energy. These indexes correspond to the input vectors of a number of independent Fuzzy ARTMAP neural networks, which aim to estimate the fault type and the power quality events that are present in the sampled signal. The input patterns of these networks are composed by energy coefficients of the first four levels of details and approximations of current and voltage signals and, the output network presents the disorder type code and the phases involved in the problem. The fault location is performed after the classification process, and the proposed technique applies to three-phase radial or weakly meshed feeders with unbalanced loads, lateral extensions triphasic, biphasic or, monophasic and presenting distributed generation. The system diagnosis and fault location proposed in this paper are able to assist the utilities in their daily works, providing important information for the operation and maintenance of power distribution systems, minimizing the repairing time and, consequently, obtaining less financial losses due to rapid fault diagnosis and restoration of the normal system operation. A real life three-phase... (Complete abstract click electronic access below)
Descrição
Palavras-chave
Sistemas de energia eletrica, Energia elétrica - Distribuição, Redes eletricas, Redes neurais (Computação), Curto-circuitos, Electric power systems
Como citar
BÍSCARO, André do Amaral Penteado. Proposta de Algoritmos Inteligentes para Localizar Faltas e Monitorar a Qualidade da Energia em Redes de Distribuição de Energia Elétrica. 2013. 156 f. Tese (doutorado) - Universidade Estadual Paulista Júlio de Mesquita Filho, Faculdade de Engenharia de Ilha Solteira, 2013.