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An Improved Lifting Morphological Wavelet Method and Its Application in Power Quality Disturbances Detection

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3 Author(s)
Wen Zhuowen ; Sch. of Electr. Power, South China Univ. of Technol., Guangzhou, China ; Ouyang Sen ; Pei Haojun

This paper proposes an improved detection method for power quality disturbances based on lifting morphological wavelet transform, which restrains the noise in the process of sampling, and accurately locates the disturbances of the power quality. Firstly, morphological extreme-value operator is chosen to construct the prediction operator and update operator, which aims to highlight the features of disturbances and restrain the noise. Secondly, the disturbing signals are dealt with the max-lifting and min-lifting morphological wavelet transform, and the detail coefficients can be obtained, which have kept the feature of disturbances of the signals. Finally, the transient disturbances of the power quality can be located through the maxima method. Simulation and on-site signal analysis show that this algorithm owns the trait of veracity, efficiency and simplicity.

Published in:

Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific

Date of Conference:

27-29 March 2012

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