New algorithm for mode shape estimation based on ambient signals considering model order selection

Using time-synchronized phasor measurements, a new signal processing approach for estimating the electromechanical mode shape properties from ambient signals is proposed. In this method, Bayesian information criterion and the ARMA(2n,2n – 1) modeling procedure are first used to automatically select the optimal model order, and the auto regressive moving averaging models are built based on ambient data, then the low-frequency oscillation modal frequency and damping ratio are identified. Next, Prony models of ambient signals are presented, and the mode shape information of multiple dominant interarea oscillation modes are simultaneously estimated. The advantages of the new ARMA-P method are demonstrated by its applications in both a simulation system and measured data from China Southern Power Grid.