Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/53496
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Type: Journal article
Title: Automatic classification and characterization of power quality events
Author: Gargoom, A.
Ertugrul, N.
Soong, W.
Citation: IEEE Transactions on Power Delivery, 2008; 23(4):2417-2425
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Issue Date: 2008
ISSN: 0885-8977
1937-4208
Statement of
Responsibility: 
Ameen M. Gargoom, Nesimi Ertugrul and Wen. L. Soong
Abstract: This paper presents a new technique for automatic monitoring of power quality events, which is based on the multiresolution S-transform and Parseval's theorem. In the proposed technique, the S-transform is used to produce instantaneous frequency vectors of the signals, and then the energies of these vectors, based on the Parseval's theorem, are utilized for automatically monitoring and classification of power quality events. The advantage of the proposed algorithm is its ability to distinguish different power quality classes easily. In addition, the magnitude, duration, and frequency content of the disturbances can be accurately identified in order to characterize the disturbances. The paper provides the theoretical background of the technique and presents a wide range of analyses to demonstrate its effectiveness.
Keywords: Automatic classification; Parseval’s theorem; power quality monitoring; S-transform
Description: Copyright © 2008 IEEE
RMID: 0020082907
DOI: 10.1109/TPWRD.2008.923998
Appears in Collections:Electrical and Electronic Engineering publications
Environment Institute publications

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