Disturbance detection for optimal database storage in electrical distribution systems using artificial immune systems with negative selection
Nenhuma Miniatura disponível
Data
2014-04-01
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Elsevier B.V.
Tipo
Artigo
Direito de acesso
Acesso restrito
Resumo
This paper presents the development of an intelligent system named normal pass filter to generate a disturbance database in electrical distribution systems. This is a system that aims to extract examples (and proper registration) of real disturbances from voltage and current measurements that are available by SCADA system. This filter is developed based on negative-selection artificial immune systems. The negative selection algorithm of an immune system is used to determine the presence of abnormalities. If an abnormality is detected, the system records the abnormal signal in a database. This database is a set of disturbance examples (e.g., harmonic, sag, high-impedance fault) for use in many purposes, for example, for training artificial neural networks for intelligent fault diagnosis and prognosis of electrical distribution systems. Recently, these diagnosis systems have been emphasized, particularly in smart grid environments. To exemplify the efficiency of the method, two electrical distribution systems with 33, and 134 busses were examined. (C) 2013 Elsevier B.V. All rights reserved.
Descrição
Palavras-chave
Idioma
Inglês
Como citar
Electric Power Systems Research. Lausanne: Elsevier Science Sa, v. 109, p. 54-62, 2014.