基于支持向量聚类的多机电力系统相干同步发电机辨识

Rimjhim Agrawal, D. Thukaram
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引用次数: 16

摘要

本文介绍了一种基于支持向量聚类(SVC)的新技术在大型互联多机电力系统中相干同步发电机直接识别中的应用。聚类是基于从系统扰动后发生器的时域响应中获得的相干度量。所提出的聚类算法可以集成到广域测量系统中,能够快速识别发电机的相干簇,从而构建动态等效模型。将该方法应用于一个实际的15台发电机72总线系统中,该系统相当于印度南部电网,试图证明该方法的有效性。研究了短路故障位置对相干性的影响。
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Identification of coherent synchronous generators in a Multi-Machine Power System using Support Vector Clustering
This paper illustrates the application of a new technique, based on Support Vector Clustering (SVC) for the direct identification of coherent synchronous generators in a large interconnected Multi-Machine Power Systems. The clustering is based on coherency measures, obtained from the time domain responses of the generators following system disturbances. The proposed clustering algorithm could be integrated into a wide-area measurement system that enables fast identification of coherent clusters of generators for the construction of dynamic equivalent models. An application of the proposed method is demonstrated on a practical 15 generators 72-bus system, an equivalent of Indian Southern grid in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations on coherency are also investigated.
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