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  2/2021 - 10

An Efficient and High-Speed Disturbance Detection Algorithm Design with Emphasis on Operation of Static Transfer Switch

USMAN, A. See more information about USMAN, A. on SCOPUS See more information about USMAN, A. on IEEExplore See more information about USMAN, A. on Web of Science, CHOUDHRY, M. A. See more information about CHOUDHRY, M. A. on SCOPUS See more information about CHOUDHRY, M. A. on SCOPUS See more information about CHOUDHRY, M. A. on Web of Science
 
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Download PDF pdficon (1,519 KB) | Citation | Downloads: 1,377 | Views: 790

Author keywords
power quality, power system, event detection, feature extraction, support vector machine

References keywords
power(47), quality(28), detection(21), classification(21), transfer(17), disturbances(17), switch(15), systems(13), static(13), voltage(11)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-05-31
Volume 21, Issue 2, Year 2021, On page(s): 87 - 98
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.02010
Web of Science Accession Number: 000657126200010
SCOPUS ID: 85107688230

Abstract
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Static Transfer Switch (STS) is required for high-speed transfer of essential load to the alternate power source when the main source fails due to power disturbance (PD). A fast and accurate PD detection method is required to ensure transfer time recommended by Computer Business Equipment Manufacturers Association (CBEMA) and IEEE Std. 446. This study encompasses the machine learning technique to reduce detection time for the disturbance on the preferred source. The 10 sample frames of acquired voltage signal were first differentiated and then distinctive features, i.e., Mean Absolute Deviation (MAD) and Energy (E) were extracted from the resultant frames. The features were fed to the Linear Support Vector Machine (L-SVM) classifier to detect the occurrence of PD events. The proposed approach achieved 100% accuracy for PD detection and detection time was significantly reduced. The system is robust in terms of unbalanced and marginal PDs. The system was validated using both simulated and real voltage signals. The proposed algorithm is easy to implement on an embedded system. Hence, detection time according to STS requirements can be achieved under various power system conditions.


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References Weight

Web of Science® Citations for all references: 1,548 TCR
SCOPUS® Citations for all references: 2,098 TCR

Web of Science® Average Citations per reference: 24 ACR
SCOPUS® Average Citations per reference: 33 ACR

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

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