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Abstract
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Article Information:
An Efficient Feature Extraction Method Based on Entropy for Power Quality Disturbance
P. Kailasapathi and D. Sivakumar
Corresponding Author: P. Kailasapathi
Submitted: April 29, 2014
Accepted: July 01, 2014
Published: September 25, 2014 |
Abstract:
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This study explores the applicability of entropy defined as thermodynamic state variable introduced by German Physicists Rudolf clausius and also presents the concepts and application of said state variable as a measure of system disorganization. Later an entropy-based feature Analysis method for power quality disturbance analysis has been proposed. Feature extraction of a disturbed power signal provides information that helps to detect the responsible fault for power quality disturbance. A precise and faster feature extraction tool helps power engineers to monitor and maintain power disturbances more efficiently. Firstly, the decomposition coefficients are obtained by applying 10-level wavelet multi resolution analysis to the signals (normal, sag, swell, outage, harmonic and sag with harmonic and swell with harmonic) generated by using the parametric equations. Secondly, a combined feature vector is obtained from standard deviation of these features after distinctive features for each signal are extracted by applying the energy, the Shannon entropy and the log-energy entropy methods to decomposition coefficients. Finally the entropy methods detect the different types of power quality disturbance.
Key words: Continuous wavelet transform, discrete-time continuous wavelet transform, entropy, entropy difference, minimum decomposition level, power quality, signal to noise ratio
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Cite this Reference:
P. Kailasapathi and D. Sivakumar, . An Efficient Feature Extraction Method Based on Entropy for Power Quality Disturbance. Research Journal of Applied Sciences, Engineering and Technology, (12): 1404-1418.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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