Atomic sparse decomposition based identification method for low-frequency oscillation modal parameters

For the traditional eigenvalue analysis method is not suitable for analyzing the large scale high-order system and the Fourier method and Prony algorithm are incapable of dealing with nonstationary signals, a novel method, atomic sparse decomposition, is introduced in this paper which is invented to deal with nonlinear or nonstationary signals to the analysis of low-frequency oscillations. This method obtains the optimal atom from a signal by using matching pursuits (MP) algorithm with the Gabor dictionary, and makes a search for parameters using the Newton-like method and finally identified the parameters of damped sinusoids. The simulations and example analysis indicates the feasibility and validity of the new method proposed in this paper. It also provides a new way for power system stability analysis.