DocumentCode :
1238404
Title :
Automatic Classification and Characterization of Power Quality Events
Author :
Gargoom, Ameen M. ; Ertugrul, Nesimi ; Soong, Wen L.
Author_Institution :
Dept. of Electr. & Electron. Eng., Adelaide Univ., Adelaide, SA
Volume :
23
Issue :
4
fYear :
2008
Firstpage :
2417
Lastpage :
2425
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 :
power supply quality; power system measurement; transforms; Parseval theorem; automatic monitoring; instantaneous frequency vectors; multiresolution S-transform; power quality events; Automatic classification; Parseval´s theorem; S-transform; power quality monitoring;
fLanguage :
English
Journal_Title :
Power Delivery, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8977
Type :
jour
DOI :
10.1109/TPWRD.2008.923998
Filename :
4534395
Link To Document :
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