Low-Frequency Inter-Area Mode Detection in Power System using Continuous Wavelet Transform

M. Ismail Hossain, M. Abido, M. Shafiul Alam, M. Shafiullah, Md. Al Emran, F. S. Hossain
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引用次数: 2

Abstract

Low-frequency oscillation can lead to the instability of an interconnected power system. Some power systems around the world have already seen blackout incidents because of low-frequency oscillation. Hence, identification of the low-frequency oscillation is critical to the interconnected power system. Low-frequency oscillation mode can be identified from its eigenvalue. However, it requires a true model of the large complex power system and works on the linear model under certain operating condition. The recorded signal from Phasor measurement unit (PMU) is used to apply Continuous Wavelet Transform (CWT) to identify low-frequency oscillation without prior knowledge of the complex mathematical model of the large interconnected power system. Among wavelet families, Complex Morlet mother-wavelet function is used in this work to formulate the mathematical relationship between system ringdowns low-frequency oscillation modal information and the CWT. The magnitude and phase plot of the complex-valued wavelet coefficients yield mode of the recorded signal. In this paper oscillation signal from a two-area four-machine power system is measured and then analyzed using continuous wavelet transform (CWT) technique to obtain its modal information corresponding to inter-area mode of oscillation. Finally, the linear system analysis method is used to compare the result from the proposed technique.
基于连续小波变换的电力系统低频区间模态检测
低频振荡会导致互联电力系统的不稳定。由于低频振荡,世界各地的一些电力系统已经发生了停电事件。因此,识别低频振荡对互联电力系统至关重要。低频振荡模态可由其特征值识别。然而,它需要一个大型复杂电力系统的真实模型,并在一定的运行条件下对线性模型进行研究。在不了解大型互联电力系统复杂数学模型的前提下,利用相量测量单元(PMU)记录的信号进行连续小波变换(CWT)识别低频振荡。在小波族中,本文采用复Morlet母-小波函数建立了系统环振低频振荡模态信息与CWT之间的数学关系。复值小波系数的幅值和相位图表示记录信号的模态。本文对两区四机电力系统的振荡信号进行了测量,并利用连续小波变换技术对其进行了分析,得到了相应的区域间振荡模态信息。最后,用线性系统分析法对所提技术的结果进行了比较。
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