Energy-sorted Prony analysis for identification of dominant low frequency oscillations

V. Patel, S. Bhil, Faruk Kazi, Sushama Wagh
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引用次数: 19

Abstract

In modern power system, the large size areas are interconnected for better power pooling that results in increased system inertia. However, this makes power to flow over long distances and pushing tie lines to operate closer to their maximum capacity. Operating tie lines closer to maximum capacity increases the possibility of inter-area oscillations (0.1-1 Hz) between two areas and is dominating near high load density area. The modern power system with growing interconnection creates more challenges in inter-area stability analysis. This paper proposes energy-sorted Prony method for online identification of dominant modes corresponding to Low Frequency Electromechanical Oscillations (LFEOs) in highly interconnected power system using Phasor Measurement Unit (PMU) data. The proposed method overcomes the disadvantage of higher false alarm rate of basic Prony method. This disadvantage is due to trivial modes that get introduced because of higher order system used in basic Prony method. The proposed method introduces a new methodology that uses the energy-sorted Prony that calculates the energy of all modes and sorts them according to energy content, this reduces the higher false alarm rate. To verify the effectiveness of the proposed method, a test signal and a two-area, four-machine system are used and the simulated results are presented.
基于能量排序的普罗尼分析识别低频主要振荡
在现代电力系统中,为了实现更好的电力集中,大范围的区域相互连接,导致系统惯性增大。然而,这使得电力传输距离较长,并推动输电线更接近其最大容量。接近最大容量的线路运行增加了两个区域之间区域间振荡(0.1-1 Hz)的可能性,并且在高负载密度区域附近占主导地位。现代电力系统的互联性日益增强,对区域间稳定性分析提出了更大的挑战。本文提出了利用相量测量单元(PMU)数据在线识别高度互联电力系统低频机电振荡(lfeo)优势模态的能量排序proony方法。该方法克服了基本proony方法虚警率较高的缺点。这种缺点是由于在基本proony方法中使用的高阶系统引入了平凡模态。该方法引入了一种新的方法,利用能量排序Prony计算所有模式的能量,并根据能量含量对其进行排序,从而降低了较高的虚警率。为了验证该方法的有效性,采用了一个测试信号和一个两区四机系统,并给出了仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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