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Recent Research Progress in Fault Analysis of Complex Electric Power SystemsWANG, Z. , ZHANG, Y. , ZHANG, J. , MA, J.
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complexity, graph theory, multivariate statistical analysis theory, fault analysis, electric power system
power(10), wang(7), analysis(7), electric(6), cluster(6), zhang(5), system(5), systems(4), dynamics(4)
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About this article
Date of Publication: 2010-02-27
Volume 10, Issue 1, Year 2010, On page(s): 28 - 33
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.01005
Web of Science Accession Number: 000275458900005
SCOPUS ID: 77954676685
In this paper, we adopt a novel approach to the fault analysis of complex electric power systems. Electric power system is one of the most complex artificial systems in the world. Its safe, steady, economical and reliable operating plays a very important part in guaranteeing socioeconomic development, and even in safeguarding social stability. The complexity of electric power system is determined by its characteristics about constitution, configuration, operation, organization, etc. No matter if, we adopt new analytical methods or technical means, we must have a distinct recognition of electric power system itself and its complexity, and increase analysis continuously, operation and control level. In this paper, utilizing real-time measurements of phasor measurement unit, based on graph theory and multivariate statistical analysis theory, we are using mainly Breadth-first search, Depth-first search and cluster analysis. Then, we seek for the uniform laws of marked changes of electrical quantities. Then we can carry out fast and exact analysis of fault component. Finally, we can accomplish fault isolation. According to line fault and bus-bar fault (single-phase fault, phase-to-phase fault and three-phase fault) in complex electric power systems, we have carried out a great deal of simulation experiments and obtained ideal results. These researches have proven that the faults in complex electric power systems can be explored successfully by analysis and calculation based on graph theory and multivariate statistical analysis theory.
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 Fault Identification Based on Nlpca in Complex Electrical Engineering, Zhang, Yagang, Wang, Zengping, Zhang, Jinfang, Journal of Electrical Engineering, ISSN 1335-3632, Issue 4, Volume 63, 2012.
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