Abstract：According to the nonstationarity, mutability and short duration of harmonic disturbance in power distribution system, it is difficult to localize and identify harmonic disturbance with high speed and accuracy. In order to improve localization and identification results of harmonic disturbance, a new method is proposed based on lifting wavelet and improved BP neural network. At first, the Euclidean decomposition principle is used to obtain db4 wavelet lifting scheme. Then, harmonic disturbance signal is decomposed through lifting wavelet analysis, and mutation peak of harmonic disturbance is localized using lifting wavelet modulus maxim. At last, traditional BP algorithm is improved by combining increasing momentum method with self-adaption learning rate method, and improved BP neural network is used to identify harmonic disturbance. The simulation results show that the proposed method can better localize the harmonic disturbances’ time information with high speed and accuracy, and can identify harmonic disturbance with high discrimination ratio.
何巨龙, 王根平, 刘丹, 唐友明. 配电系统谐波扰动的定位与识别研究[J]. 电气技术, 2016, 17(12): 25-30.
He Julong, Wang Genping, Liu Dan, Tang Youming. Localization and Identification Research of Harmonic Disturbance in Power Distribution System. Electrical Engineering, 2016, 17(12): 25-30.
2016, Vol. 17 
