Full-Parameters Identification Technique of Attenuated Oscillations in Power System Monitoring

It is vital to accurately identify the modal parameters of oscillation signals to control and even avoid low-frequency oscillations which threaten the stability of power system. A novel full-parameters identification technique is developed in this paper to identify all modal parameters of attenuated low-frequency oscillations based on stochastic subspace identification (SSI) and Prony algorithms by the parameter matching approach. Firstly, empirical mode decomposition (EMD) is applied to filter and smooth the oscillation signal. Then, SSI and Prony are used to identify the modal parameters by parameter matching. Through a case study with the proposed method, we find the reconstructed signal based on the modal parameters acquired are largely consistent with the original signal, by removing interference, identifying modal parameters and overcoming the weakness of single algorithm. Therefore, the proposed method can accurately identify full modal parameters of attenuated low-frequency oscillations and enhance the stability and safety of power system by monitoring and controlling oscillations.