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Coherency feature extraction based on DFT-based continuous wavelet transform

机译:基于基于DFT的连续小波变换的相干特征提取

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Coherency identification is an important issue for transient stability analysis. In this paper, a coherency feature extraction method is proposed based on DFT-based continuous wavelet transform (CWT). By analyzing several typical situations of power angle swing (including incremental oscillated, damping oscillated and swing apart) using DFT-based CWT, it is illustrated that the scale and energy percentage of main components of the original signal can reveal the similarity and difference between power angle curves of the generators. Thus transient process of power angle can be described by a few indexes instead of a series of temporal data. Finally, case study in New England 10-machine 39-bus system indicates that the proposed coherency feature is valid for coherency identification in different fault cases.
机译:相干性识别是瞬态稳定性分析的重要问题。本文提出了一种基于DFT的连续小波变换(CWT)相干特征提取方法。通过使用基于DFT的CWT分析功率角摆幅的几种典型情况(包括增量摆幅,阻尼摆幅和摆幅分开),可以说明原始信号主要成分的比例和能量百分比可以揭示功率之间的相似性和差异性发电机的角度曲线。因此,可以通过几个指标而不是一系列时间数据来描述功率角的瞬态过程。最后,在新英格兰10机39总线系统中的案例研究表明,所提出的相干性特征对于不同故障情况下的相干性识别是有效的。

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