Associate Hermite Expansion Small Signal Mode Estimation

Many methods have been proposed to assess small signal stability for either analysis or control purposes. In this paper, a new offline method is proposed to detect electromechanical modes and their associated damping levels in power systems. The new method estimates oscillatory performance by fitting an orthogonal polynomial expansion to data and extrapolating its spectrum to identify low frequency modes. Damping of individual modes is then performed using a sliding window technique previously developed with the use of a linear prediction algorithm. Performance of the new technique is assessed using test signals and measurements recorded from staged field tests along with noise probing measurements. Accuracy of the new method is measured against a least squares Prony algorithm and the Yule-Walker autoregressive technique using identical data sets. Estimation results reveal that the new method is reasonably accurate in the detection of modes and their damping levels when compared to other methods.