Identification of low frequency oscillation parameters based on EEMD-SVD method and Prony algorithm

With the development of the economy, the scale and complexity of the power system have greatly increased, and the problem of low-frequency oscillation has increased. Therefore, to address this issue, this paper proposed the mechanism of the Prony algorithm. In this paper, The parameters of low-frequency oscillation are extracted by the Prony algorithm, the characteristics and principles of the Prony algorithm are introduced, and the order of the model, the sampling frequency and the choice of time length in practical applications are considered. At the same time, in order to solve the problem of the poor sensitivity of Prony algorithm, the method of combining ensemble empirical mode decomposition (EEMD) and singular value decomposition (SVD) was proposed to improve the signal-to-noise ratio. Through MATLAB simulation, in the presence of noise interference, Prony algorithm can accurately identify the various mode parameters of low-frequency oscillations.