Monitoring HVDC systems using wavelet multi-resolution analysis

Author

Gaouda, A.M. ; El-Saadany, E.F. ; Salama, M.M.A. ; Sood, V.K. ; Chikhani, A.Y.

Author_Institution

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

Volume

16

Issue

4

fYear

2001

fDate

11/1/2001 12:00:00 AM

Firstpage

662

Lastpage

670

Abstract

The paper presents a disturbance classification technique based on wavelet multi-resolution analysis. The wavelet multi-resolution transform is introduced as a tool for providing discriminative, translation-invariant features with small dimensions to classify different disturbances in an HVDC transmission system. The proposed method extracts features from signals monitored on both DC and AC sides of the HVDC system. It is shown that monitored signals show promising features that can classify different disturbances that may occur anywhere in the HVDC system

Keywords

HVDC power transmission; feature extraction; monitoring; signal processing; wavelet transforms; HVDC systems monitoring; HVDC transmission system; commutation failure; discriminative translation-invariant features; disturbance classification technique; feature extraction; multiresolution signal decomposition; wavelet multi-resolution analysis; Condition monitoring; Counting circuits; Feature extraction; HVDC transmission; Multiresolution analysis; Neural networks; Power quality; Signal analysis; Signal resolution; Wavelet analysis;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.962411

Filename

962411