ESPRIT analysis of subsynchronous oscillation based on the empirical mode decomposition self-adaptive filter

Estimation of signal parameters via rotational invariance techniques(ESPRIT)can be used to identify subsynchronous oscillation. However,this method can't identify mode parameter efficiently in the noise. This paper uses the empirical mode decomposition (EMD) method to filter the noise before the parameters are identified. And then, the improved ESPRIT is compared with the non-filtered ESPRIT and the PRONY algorithm in order to prove its availability. Simulation results show that using empirical mode decomposition, self-adaptive filter can be realized and the veracity is improved. In consideration of the self-adaptibility of EMD and the speediness and accuracy of ESPRIT identification, the proposed method can be applied to on-line detection of subsynchronous oscillation (SSO), laying a foundation for the monitor and research of SSO of large system.