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JCR Impact Factor: 0.595
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Issues per year: 4
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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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2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

2017-Jan-30
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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  2/2012 - 4

A Novel Fault Identification Using WAMS/PMU

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
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (761 KB) | Citation | Downloads: 719 | Views: 2,951

Author keywords
fault identification, noise, principal component analysis, wide area measurement system, wams

References keywords
power(12), systems(11), zhang(9), analysis(8), fault(7), wang(6), electric(6), research(5), principal(4)
Blue keywords are present in both the references section and the paper title.

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

Abstract
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Full text preview
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.


References | Cited By  «-- Click to see who has cited this paper

[1] A.G. Phadke and J.S. Thorp, "Expose hidden failures to prevent cascading outages," IEEE Computer Applications in Power, vol.9, pp. 20-23, Jul. 1996
[CrossRef] [Web of Science Times Cited 92] [SCOPUS Times Cited 191]


[2] A.G. Phadke and J.S. Thorp, Synchronized phasor measurements and their applications, Springer verlag, 2008.

[3] Y. G. Zhang, Z. P. Wang, J. F. Zhang and J. Ma, "Fault localization in electrical power systems: A pattern recognition approach," International Journal of Electric Power & Energy Systems, vol.33, pp.791-798, Mar. 2011
[CrossRef] [Web of Science Times Cited 43] [SCOPUS Times Cited 58]


[4] C. Wang, Q. Q. Jia, X. B. Li and C. X. Dou, "Fault location using synchronized sequence measurements," International Journal of Electrical Power & Energy Systems, vol.30. pp. 134-139, Feb.2008
[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 30]


[5] T. S. Bi, X. H. Qin and Q. X. Yang, "A novel hybrid state estimator for including synchronized phasor measurements," Electric Power Systems Research, vol.78, pp. 1343-1352, Aug. 2008
[CrossRef] [Web of Science Times Cited 61] [SCOPUS Times Cited 83]


[6] C. Wang, C. X. Dou, X. B. Li and Q. Q. Jia, "A WAMS/PMU-based fault location technique," Electric Power Systems Research, vol. 77, pp. 936-945, Jun. 2007
[CrossRef] [Web of Science Times Cited 26] [SCOPUS Times Cited 38]


[7] Z. P. Wang, Y. G. Zhang and J. F. Zhang, "Recent research progress in fault analysis of complex electric power systems," Advances in Electrical and Computer Engineering, vol.10, pp.28-33, Feb. 2010
[CrossRef] [Full Text] [Web of Science Times Cited 15] [SCOPUS Times Cited 21]


[8] L. X. Dong, D. M. Xiao, Y. S. Liang and Y. L. Liu, "Rough set and fuzzy wavelet neural network integrated with least square weighted fusion algorithm based fault diagnosis research for power transformers," Electric Power Systems Research, vol.78, pp. 129-136, Jan. 2008
[CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 58]


[9] Y. G. Zhang, Z. P. Wang, J. F. Zhang and J. Ma, "PCA fault feature extraction in complex electric power systems," Advances in Electrical and Computer Engineering, vol.10, pp.102-107, Aug. 2010
[CrossRef] [Full Text] [Web of Science Times Cited 14] [SCOPUS Times Cited 18]


[10] P. Giordania and H. Kiersb, "Principal component analysis of symmetric fuzzy data," Computational Statistics & Data Analysis, vol.45, pp. 519-548, Apr. 2004
[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 28]


[11] P. L. Cui, J. H. Li and G. Z. Wang, "Improved kernel principal component analysis for fault detection," Expert Systems with Applications, vol.34, pp. 1210-1219, Feb. 2008
[CrossRef] [Web of Science Times Cited 39] [SCOPUS Times Cited 59]


[12] C. D. Lu, C. M Zhang, T. Y. Zhang and W. Zhang, "Kernel based symmetrical principal component analysis for face classification," Neurocomputing, vol.70, pp. 904-911, Jan. 2007
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 16]


[13] M.A. Perry, H.P. Wynn and R.A. Bates, "Principal components analysis in sensitivity studies of dynamic systems," Probabilistic Engineering Mechanics, vol. 21, pp. 454-460, Oct. 2006
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 11]


[14] A. G. Phadke and J. S. Thorp, Computer relaying for power system, Second edition, John Wiley & Sons Ltd, Chichester, 2009.

[15] R. Johnson and D. Wichern, Applied multivariate statistical analysis, Prentice Hall, London, 2002.

[16] J. P. Zhu, Applied multivariate statistical analysis, Science Press, Beijing, 2006.

[17] D. Johnson, Applied multivariate methods for data analysts, Duxbury Press, Pacific Grove, CA, 1998.

[18] IEEE Std C37.118TM-2005, IEEE standard for synchrophasors for power systems, IEEE, New York, 2006.



References Weight

Web of Science® Citations for all references: 392 TCR
SCOPUS® Citations for all references: 611 TCR

Web of Science® Average Citations per reference: 21 ACR
SCOPUS® Average Citations per reference: 32 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-06-27 21:18 in 93 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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