王金浩, 刘愈倬, 薛 磊, 等. 基于dq变换、小波变换及FFT的电能质量扰动识别[J]. 现代电力, 2010, 27(3): 16-20.
引用本文: 王金浩, 刘愈倬, 薛 磊, 等. 基于dq变换、小波变换及FFT的电能质量扰动识别[J]. 现代电力, 2010, 27(3): 16-20.
Wang Jinhao, Liu Yuzhuo, Xue Lei, et al. Power Quality Disturbance Identification Based on dq Conversion, Wavelet Transform and FFT[J]. Modern Electric Power, 2010, 27(3): 16-20.
Citation: Wang Jinhao, Liu Yuzhuo, Xue Lei, et al. Power Quality Disturbance Identification Based on dq Conversion, Wavelet Transform and FFT[J]. Modern Electric Power, 2010, 27(3): 16-20.

基于dq变换、小波变换及FFT的电能质量扰动识别

Power Quality Disturbance Identification Based on dq Conversion, Wavelet Transform and FFT

  • 摘要: 利用dq变换有效值波形特征、小波变换和FFT对7种电能质量扰动信号进行分层次识别并求其取特征参数。首先根据扰动信号电压有效值的分布特性将扰动分为两类:电压暂降、暂升和中断为第1类:谐波、瞬态脉冲、低频振荡、电压波动为第2类。然后对第2类扰动进行小波多分辨率分析, 由高频系数特征识别出瞬态脉冲和低频振荡, 通过过零点个数将两者区分。最后再对小波变换后高频系数呈现相似分布的谐波和电压波动进行FFT变换, 用频谱特性进行识别。该方法不仅能够有效识别扰动类型, 同时还能够求出电压暂降等扰动的起止时刻和幅值, 瞬态脉冲和低频振荡的峰值、峰值时刻等特征参数。仿真实验结果表明了该方法的有效性。

     

    Abstract: Using the waveform characteristics of the valid values by dq conversion, wavelet transform and FFT, seven types of power quality disturbances are layered recognized, and their characteristic parameters are obtained.According to the distribution characters of the valid values of the disturbance signal, the disturbances are divided into two types. The first type includes voltage sag, swell and interruption. The second type includes harmonic, transient pulse, low frequency oscillation and voltage fluctuation.The multi resolution analysis is carried out for the second disturbances. The transient pulse and low frequency oscillation are identified by the characteristics of the high frequency coefficients, and then they can be separated by the number of zero crossing points.After FFT transform, harmonic and voltage fluctuation, whose high frequency coefficients distributions are similar. They can be identified according to spectrum characteristics. The proposed method can effectively identify the disturbance types and obtain their characteristic parameters, such as the starting and ending time and amplitude of voltage sag, the peak and peak times of transient pulse and low frequency oscillation. Simulation results show the effectiveness of the proposed method.

     

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