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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2010 - 17

 HIGH-IMPACT PAPER 

PCA Fault Feature Extraction in Complex Electric Power Systems

ZHANG, Y. See more information about ZHANG, Y. on SCOPUS See more information about ZHANG, Y. on IEEExplore See more information about ZHANG, Y. on Web of Science, WANG, Z. See more information about  WANG, Z. on SCOPUS See more information about  WANG, Z. on SCOPUS See more information about WANG, Z. on Web of Science, ZHANG, J. See more information about  ZHANG, J. on SCOPUS See more information about  ZHANG, J. on SCOPUS See more information about ZHANG, J. on Web of Science, MA, J. See more information about MA, J. on SCOPUS See more information about MA, J. on SCOPUS See more information about MA, J. on Web of Science
 
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Download PDF pdficon (575 KB) | Citation | Downloads: 1,624 | Views: 5,788

Author keywords
complexity, fault feature extraction, principal components analysis, PCA, phasor measurement unit, PMU, electric power system

References keywords
power(11), electric(7), analysis(6), systems(5), system(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-08-31
Volume 10, Issue 3, Year 2010, On page(s): 102 - 107
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.03017
Web of Science Accession Number: 000281805600017
SCOPUS ID: 77956623447

Abstract
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Electric power system is one of the most complex artificial systems in the world. The complexity is determined by its characteristics about constitution, configuration, operation, organization, etc. The fault in electric power system cannot be completely avoided. When electric power system operates from normal state to failure or abnormal, its electric quantities (current, voltage and angles, etc.) may change significantly. Our researches indicate that the variable with the biggest coefficient in principal component usually corresponds to the fault. Therefore, utilizing real-time measurements of phasor measurement unit, based on principal components analysis technology, we have extracted successfully the distinct features of fault component. Of course, because of the complexity of different types of faults in electric power system, there still exists enormous problems need a close and intensive study.


References | Cited By

Cited-By Clarivate Web of Science

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Cited-By SCOPUS

SCOPUS® Times Cited: 20
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Cited-By CrossRef

[1] Fault Monitoring Based on the VLSW-MADF Test and DLPPCA for Multimodal Processes, Wang, Shu, Wang, Yicheng, Tong, Jiarong, Chang, Yuqing, Sensors, ISSN 1424-8220, Issue 2, Volume 23, 2023.
Digital Object Identifier: 10.3390/s23020987
[CrossRef]

[2] Dimensionality Reduction of Synchrophasor Data for Early Event Detection: Linearized Analysis, Xie, Le, Chen, Yang, Kumar, P. R., IEEE Transactions on Power Systems, ISSN 0885-8950, Issue 6, Volume 29, 2014.
Digital Object Identifier: 10.1109/TPWRS.2014.2316476
[CrossRef]

[3] A Data-Driven Approach for Estimating the Power Generation of Invisible Solar Sites, Shaker, Hamid, Zareipour, Hamidreza, Wood, David, IEEE Transactions on Smart Grid, ISSN 1949-3053, Issue 5, Volume 7, 2016.
Digital Object Identifier: 10.1109/TSG.2015.2502140
[CrossRef]

[4] Bayes-Based Fault Discrimination in Wide Area Backup Protection, WANG, Z., ZHANG, J., ZHANG, Y., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 12, 2012.
Digital Object Identifier: 10.4316/aece.2012.01015
[CrossRef] [Full text]

[5] Anatomization of the systems of dimension relaxation for facial recognition, Raha, Mayamin Hamid, Deb, Tonmoay, Rahmun, Mahieyin, Chen, Tim, Intelligent Decision Technologies, ISSN 1872-4981, Issue 4, Volume 14, 2021.
Digital Object Identifier: 10.3233/IDT-190120
[CrossRef]

[6] Fault localization in electrical power systems: A pattern recognition approach, Zhang, Ya-Gang, Wang, Zeng-Ping, Zhang, Jin-Fang, Ma, Jing, International Journal of Electrical Power & Energy Systems, ISSN 0142-0615, Issue 3, Volume 33, 2011.
Digital Object Identifier: 10.1016/j.ijepes.2011.01.018
[CrossRef]

[7] 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.
Digital Object Identifier: 10.2478/v10187-012-0036-4
[CrossRef]

[8] A Novel Fault Identification Using WAMS/PMU, ZHANG, Y., WANG, Z., ZHANG, J., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 2, Volume 12, 2012.
Digital Object Identifier: 10.4316/aece.2012.02004
[CrossRef] [Full text]

[9] Bifurcation criterion of faults in complex nonlinear systems, Zhang, Yagang, Wang, Zengping, Physics Letters A, ISSN 0375-9601, Issue 18-19, Volume 378, 2014.
Digital Object Identifier: 10.1016/j.physleta.2014.02.038
[CrossRef]

[10] Posterior probability locates faults under the influence of new energy resources, Yagang Zhang, , Zengping Wang, , Jinfang Zhang,, 2012 IEEE Power and Energy Society General Meeting, ISBN 978-1-4673-2729-9, 2012.
Digital Object Identifier: 10.1109/PESGM.2012.6345258
[CrossRef]

[11] Principal components fault location based on WAMS/PMU measure system, Wang, Zengping, Zhang, Yagang, Zhang, Jinfang, 2011 IEEE Power and Energy Society General Meeting, ISBN 978-1-4577-1000-1, 2011.
Digital Object Identifier: 10.1109/PES.2011.6039102
[CrossRef]

[12] Dimensionality reduction and early event detection using online synchrophasor data, Yang Chen, , Le Xie, , Kumar, P. R., 2013 IEEE Power & Energy Society General Meeting, ISBN 978-1-4799-1303-9, 2013.
Digital Object Identifier: 10.1109/PESMG.2013.6672974
[CrossRef]

[13] Bayesian fault detection based on WAMS/PMU measurement system, Yagang Zhang, , Zengping Wang, , Jinfang Zhang,, 2012 IEEE Power and Energy Society General Meeting, ISBN 978-1-4673-2729-9, 2012.
Digital Object Identifier: 10.1109/PESGM.2012.6345199
[CrossRef]

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