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Power Quality Disturbance Auto Recognition Based on Wavelet and Artificial Neural Network

Author: ZhangZhiYuan
Tutor: LiGengYin
School: North China Electric Power University
Course: Proceedings of the
Keywords: Power Quality Dynamic disturbance identification and location Wavelet Transform Genetic Algorithms
CLC: TM732
Type: Master's thesis
Year: 2002
Downloads: 251
Quote: 6
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Abstract


For power system dynamic power quality disturbance is proposed based on wavelet and evolutionary networks of power quality disturbance automatic identification method , first applied Daubechies 3 wavelet decomposition of the disturbance waveform , and then feature extraction, and the use of design patterns based on genetic algorithm feature classifier to classify the disturbance , experiments show that this method has classification accuracy , network learning speed and convergence effect and other notable features . According to transmission line differential protection principle , but also presents a dynamic power quality disturbance source localization method , by defining the disturbance energy , more measurement points on the line corresponding to the direction of the disturbance energy , determine the location of the disturbance source . Using Simulink toolbox for IEEE 9 bus system simulation , through the different sources of disturbance switching analyzed to verify the correctness of the method .

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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Power system scheduling, management, communication > The operation of the power system
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