Title :
A power harmonic detection method based on Wavelet Neural Network
Author :
Mu Haiwei ; Ma Na ; Fu Guangjie ; Liu Xianglou
Author_Institution :
Electron. Sci. Coll., Daqing Pet. Inst., Daqing, China
Abstract :
Harmonic detection technology is one of the key technologies used for active power filter (APF), its development has determined the development of APF technology. It is difficult to detect the harmonic accurately because of the features of power network harmonic, such as inherent nonlinear, random, distribution, non-stationary and the complexity of impact factors, so the study of the power system harmonic´s detection methods is very important. This paper proposes a harmonic detection method based on Wavelet Neural Network combining Wavelet with Neural Network, and designs for the wavelet neural network. The simulation results show that this method can detect the power network harmonic accurately and real-time.
Keywords :
active filters; neural nets; power engineering computing; power filters; power system harmonics; wavelet transforms; active power filter; impact factors; power harmonic detection; power network harmonic; power system harmonic detection; wavelet neural network; Active filters; Artificial neural networks; Educational institutions; Harmonic analysis; Petroleum; Power harmonic filters; Harmonic Detection; Simulation Research; Wavelet Neural Network;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6