Power quality detection and classification using wavelet-multiresolution signal decomposition

Author

Gaouda, A.M. ; Salama, Magdy M. A. ; Sultan, M.K. ; Chikhani, A.Y.

Author_Institution

Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada

Volume

14

Issue

4

fYear

1999

fDate

10/1/1999 12:00:00 AM

Firstpage

1469

Lastpage

1476

Abstract

The wavelet transform is introduced as a powerful tool for monitoring power quality problems generated due to the dynamic performance of industrial plants. The paper presents a multiresolution signal decomposition technique as an efficient method in analyzing transient events. The multiresolution signal decomposition has the ability to detect and localize transient events and furthermore classify different power quality disturbances. It can also be used to distinguish among similar disturbances

Keywords

industrial power systems; power supply quality; power system faults; power system measurement; wavelet transforms; dynamic performance; industrial plants; multiresolution signal decomposition; power quality detection; power quality detection and classification; power quality disturbances; power system monitoring; wavelet-multiresolution signal decomposition; Computerized monitoring; Educational institutions; Military computing; Multiresolution analysis; Power quality; Signal analysis; Signal resolution; Voltage fluctuations; Wavelet analysis; Wavelet transforms;

fLanguage

English

Journal_Title

Power Delivery, IEEE Transactions on

Publisher

ieee

ISSN

0885-8977

Type

jour

DOI

10.1109/61.796242

Filename

796242