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