Identification of interarea modes from ringdown data by curve-fitting in the frequency domain

Low damping ratios of interarea modes in the power system result in peaks at their natural frequencies in the discrete Fourier transform (DFT) representation of ringdown data. This has been a motivation to develop a nonparametric DFT-based modal identification method. However, this method has difficulty estimating damping ratios. This paper proposes a parametric DFT-based method to solve such a problem in the non-parametric one. To effectively remove the decaying dc component in ringdown data, the proposed method uses a difference sequence between two sets of ringdown frequency data with oscillation against each other. This method estimates coefficients of the numerator and denominator in the Laplace transform of the frequency difference sequence by curve-fitting of DFT values around peak frequencies. Then, modal natural frequencies and damping ratios are calculated from estimated coefficients of the denominator. This method is compared to a non-parametric DFT-based method and a Prony-based method through simulations on the signal-to-noise ratio and is applied to identify real power systems from ringdown frequency data in the Frequency Monitoring Network system.