DocumentCode :
2095976
Title :
Power Quality Disturbances Identification Based on dq Conversion, Wavelet Transform and FFT
Author :
Zhao Yan ; Xu Yonghai ; Xiao Xiangning ; Zhu Yongqiang ; Guo Chunlin
Author_Institution :
Dept. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
fYear :
2010
fDate :
28-31 March 2010
Firstpage :
1
Lastpage :
4
Abstract :
Based on the waveform characteristic of virtual value by dq conversion, Wavelet Analysis and FFT, seven types of power quality disturbances are layered-recognized. Firstly, according to the size of voltage virtual value, the disturbances will be divided into two types, the first type includes voltage sag, swell and interruption. The second type includes the rest of the disturbances. Secondly, wavelet analysis will be carried out to the second type, transient pulse and low frequency oscillation will be identified by the characteristic of high frequency coefficient and then they will be separated by the number of zero-crossing points. Finally, as far as the disturbances, which present similar distribution in high frequency coefficient, as the comparability, FFT can be used. We can identify them with spectrum characteristic. Simulation results show the effectiveness of the proposed method.
Keywords :
fast Fourier transforms; power supply quality; wavelet transforms; FFT; dq conversion; low frequency oscillation; power quality disturbances identification; transient pulse; voltage sag; wavelet analysis; wavelet transform; zero-crossing points; Discrete wavelet transforms; Equations; Power engineering and energy; Power quality; Time domain analysis; Time frequency analysis; Transient analysis; Voltage fluctuations; Wavelet analysis; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2010 Asia-Pacific
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4812-8
Electronic_ISBN :
978-1-4244-4813-5
Type :
conf
DOI :
10.1109/APPEEC.2010.5448526
Filename :
5448526
Link To Document :
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