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Automatic Classification and Characterization of Power Quality Events

Citation

Gargoom, AMM and Ertugrul, N and Soong, WL, Automatic Classification and Characterization of Power Quality Events, IEEE Transactions on Power Delivery, 23, (4) pp. 2417-2425. ISSN 0885-8977 (2008) [Refereed Article]

DOI: doi:10.1109/TPWRD.2008.923998

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. © 2008 IEEE.

Item Details

Item Type:Refereed Article
Research Division:Engineering
Research Group:Electrical and Electronic Engineering
Research Field:Control Systems, Robotics and Automation
Objective Division:Energy
Objective Group:Other Energy
Objective Field:Energy not elsewhere classified
Author:Gargoom, AMM (Dr Ameen Gargoom)
ID Code:55354
Year Published:2008
Web of Science® Times Cited:40
Deposited By:Centre for Renewable Power Energy Systems
Deposited On:2009-03-09
Last Modified:2009-09-03
Downloads:0

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