|2/2012 - 4|
A Novel Fault Identification Using WAMS/PMUZHANG, Y. , WANG, Z. , ZHANG, J.
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fault identification, noise, principal component analysis, wide area measurement system, wams
power(12), systems(11), zhang(9), analysis(8), fault(7), wang(6), electric(6), research(5), principal(4)
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About this article
Date of Publication: 2012-05-30
Volume 12, Issue 2, Year 2012, On page(s): 21 - 26
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.02004
Web of Science Accession Number: 000305608000004
SCOPUS ID: 84865279517
The important premise of the novel adaptive backup protection based on wide area information is to identify the fault in a real-time and on-line way. In this paper, the principal components analysis theory is introduced into the field of fault detection to locate precisely the fault by mean of the voltage and current phasor data from the PMUs. Massive simulation experiments have fully proven that the fault identification can be performed successfully by principal component analysis and calculation. Our researches indicate that the variable with the biggest coefficient in principal component usually corresponds to the fault. Under the influence of noise, the results are still accurate and reliable. So, the principal components fault identification has strong anti-interference ability and great redundancy.
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 A Multi-objective PMU Placement Method Considering Observability and Measurement Redundancy using ABC Algorithm, KULANTHAISAMY, A., VAIRAMANI, R., KARUNAMURTHI, N. K., KOODALSAMY, C., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 14, 2014.
Digital Object Identifier: 10.4316/AECE.2014.02020 [CrossRef] [Full text]
 Experimental System for Monitoring and Diagnosis of a Static Power Converter, IVANOV, V. I., BROJBOIU, M. D., IVANOV, S. S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.02018 [CrossRef] [Full text]
 New Fault Discrimination under the Influence of Rayleigh Noise, ZHANG, Y., WANG, Z., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.03005 [CrossRef] [Full text]
 Fault factor analysis with phasor measurement units, Zhang, Yagang, Wang, Zengping, 2014 IEEE PES General Meeting | Conference & Exposition, ISBN 978-1-4799-6415-4, 2014.
Digital Object Identifier: 10.1109/PESGM.2014.6939400 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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