主成分分析与proony分析相结合用于机电振荡辨识

Alessandro Bosisio, A. Berizzi, G. Moraes, R. Nebuloni, G. Giannuzzi, R. Zaottini, C. Maiolini
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引用次数: 4

摘要

本文提出了一种基于主成分分析(PCA)的机电振荡辨识方法。所提出的方法使得对有限数量的所谓主分量(PCs)进行分析成为可能,从而获得在小扰动后母线电压和电流行为的信息。分析是利用pc上的proony分析完成的,它能够确定一个模态的振幅、频率和阻尼。为了评估该方法的有效性,将该算法应用于基于Kundur双区系统的测试系统以及实际事件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Combined use of PCA and Prony Analysis for Electromechanical Oscillation Identification
In this study, a new PMU-based method of identification of electromechanical oscillations is presented exploiting Principal Components Analysis (PCA). The proposed method makes it possible to carry out analysis on a limited number of the so-called Princial Components (PCs), obtaining information on the behavior of voltages and currents at buses following a small perturbation. The analysis is completed using the Prony analysis on the PCs, which is able to determine the amplitude, frequency and damping of a mode. To assess the effectiveness of the method, the algorithm has been applied on a test system based on the Kundur Two-area system as well as on a real event.
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