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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: May 2018
Next issue: Aug 2018
Avg review time: 105 days


PUBLISHER

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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LATEST NEWS

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-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

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  4/2017 - 5

Fault Localization for Synchrophasor Data using Kernel Principal Component Analysis

CHEN, R. See more information about CHEN, R. on SCOPUS See more information about CHEN, R. on IEEExplore See more information about CHEN, R. on Web of Science, SUN, X. See more information about  SUN, X. on SCOPUS See more information about  SUN, X. on SCOPUS See more information about SUN, X. on Web of Science, LIU, G. See more information about LIU, G. on SCOPUS See more information about LIU, G. on SCOPUS See more information about LIU, G. 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 (1,213 KB) | Citation | Downloads: 243 | Views: 340

Author keywords
power systems, fault location, phasor measurement units, kernel, principal component analysis

References keywords
power(17), systems(10), analysis(10), detection(9), system(7), component(7), fault(6), principal(5), kernel(4), components(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-11-30
Volume 17, Issue 4, Year 2017, On page(s): 37 - 42
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.04005
Web of Science Accession Number: 000417674300005
SCOPUS ID: 85035786014

Abstract
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In this paper, based on Kernel Principal Component Analysis (KPCA) of Phasor Measurement Units (PMU) data, a nonlinear method is proposed for fault location in complex power systems. Resorting to the scaling factor, the derivative for a polynomial kernel is obtained. Then, the contribution of each variable to the T2 statistic is derived to determine whether a bus is the fault component. Compared to the previous Principal Component Analysis (PCA) based methods, the novel version can combat the characteristic of strong nonlinearity, and provide the precise identification of fault location. Computer simulations are conducted to demonstrate the improved performance in recognizing the fault component and evaluating its propagation across the system based on the proposed method.


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Copyright ©2001-2018
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

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