Title :
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
fDate :
1/1/2002 12:00:00 AM
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;
Journal_Title :
Power Delivery, IEEE Transactions on
