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Power Quality Disturbance Research of Grid-connected Wind Generation Based on Fractional Fourier Transform with Wavelet Entropy

机译:基于小波熵的分数阶傅里叶变换的并网风力发电电能质量扰动研究

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In the process of connected wind generation with the power grid, the classification and recognition of power quality disturbance signals which are researched by the scholars at home and abroad are always the hot issues in Power System. A new method using Fractional Fourier Transform (FRFT) with Wavelet Entropy is presented for recognizing the signals of PQ disturbance based on the characteristics of power quality (PQ) signals. FRFT have better time-frequency aggregation and can choose better domain μ instead of ω and make PQ disturbance recognize more accurately with wavelet entropy. Simulation results demonstrate its effectiveness.
机译:在电网并网发电过程中,国内外学者研究的电能质量扰动信号的分类与识别一直是电力系统中的热点问题。提出了一种结合小波熵的分数阶傅里叶变换(FRFT)方法,根据电能质量(PQ)信号的特征来识别PQ干扰信号。 FRFT具有更好的时频聚集,可以选择更好的域μ而不是ω,并利用小波熵使PQ扰动更准确地识别。仿真结果证明了其有效性。

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