Power disturbance classifier using a rule-based method and wavelet packet-based hidden Markov model

Author

Chung, Jaehak ; Powers, Edward J. ; Grady, W. Mack ; Bhatt, Siddharth C.

Author_Institution

Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA

Volume

17

Issue

1

fYear

2002

fDate

1/1/2002 12:00:00 AM

Firstpage

233

Lastpage

241

Abstract

This paper presents a novel classification method for power distribution line disturbances using a rule-based method and a wavelet packet-based hidden Markov model (HMM). The rule-based method is utilized for the classification of time-characterized-feature disturbances, and the wavelet packet-based HMM is utilized for the frequency-characterized-feature power disturbances. This proposed method classifies six types of actual recorded power distribution disturbances, i.e., sag, interruption, fast capacitor switching, capacitor switching, normal variation, and impulse disturbance, and obtains 98.7% correct classification rate for 670 actual disturbance events tested

Keywords

capacitor switching; hidden Markov models; knowledge based systems; power distribution faults; power distribution lines; wavelet transforms; capacitor switching; fast capacitor switching; frequency-characterized-feature power disturbances; impulse disturbance; interruption; normal variation; power distribution line disturbances; power disturbance classifier; rule-based method; sag; time-characterized-feature disturbances; wavelet packet-based hidden Markov model; Capacitors; Data mining; Frequency; Hidden Markov models; Neural networks; Power quality; Power transmission lines; Transmission line theory; Wavelet packets; Wavelet transforms;

fLanguage

English

Journal_Title

Power Delivery, IEEE Transactions on

Publisher

ieee

ISSN

0885-8977

Type

jour

DOI

10.1109/61.974212

Filename

974212