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Coherency feature extraction based on DFT-based continuous wavelet transform

机译:基于DFT的连续小波变换的一致性特征提取

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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:一致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基连续小波变换(CWT)的一致性特征提取方法。通过分析使用基于DFT的CWT的电源角度摆动(包括增量振荡,阻尼,阻尼振荡和摆动)的几种典型情况,示出了原始信号的主要部件的比例和能量百分比可以揭示电力之间的相似性和差异发电机的角度曲线。因此,电源角的瞬态过程可以由几个索引而不是一系列时间数据来描述。最后,在新英格兰10机器39总线系统中的案例研究表明,所提出的一致性功能对于不同故障情况下的一致性识别是有效的。

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