Low-frequency oscillations in power systems can be modeled as an exponentially damped sinusoid (EDS) signal. Its frequency, damping factor, and amplitude are identified by the robust algorithm proposed in this paper. Under the condition of no noise, the exponentially convergent property of the proposed identification is proved by the use of time scale change, variable transformation, slow integral manifold, averaging method, and Lyapunov stability theorem in sequence. Under the condition of bounded additive noise, the antinoise performance of the identification of each parameter is investigated by the perturbed system theorem and error synthesis principle. The robustness of the proposed method is embodied in the following aspects: the exponential convergence for EDS signal with a wide range of frequency, especially with a rather low frequency; the boundary values of identification errors resulting from high-frequency sinusoidal noise of both frequency and damping factor can be adjusted by tuning the design parameters; and the different effects of the four design parameters on tracking performance and antinoise performance of each parameter identification. Simulation results demonstrate the performance of the algorithm and validate the conclusions.

中文翻译：

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电力系统指数阻尼低频振荡的鲁棒直接参数辨识

电力系统中的低频振荡可以建模为指数阻尼正弦波（EDS）信号。通过本文提出的鲁棒算法可以确定其频率，阻尼系数和幅度。在无噪声的条件下，通过时间尺度变化，变量变换，慢积分流形，均值方法和Lyapunov稳定性定理依次证明了所提出识别的指数收敛性质。在有界加性噪声的条件下，利用扰动系统定理和误差综合原理研究了各参数辨识的抗噪性能。所提出的方法的鲁棒性体现在以下几个方面：频率范围宽，尤其是频率相对较低的EDS信号的指数收敛；可以通过调整设计参数来调整由频率和阻尼因数的高频正弦噪声引起的识别误差的边界值；以及四个设计参数对每个参数识别的跟踪性能和抗噪声性能的不同影响。仿真结果证明了该算法的性能并验证了结论。