Estimation of low-frequency modes in power system using robust modified Prony

This study proposes to modify improved Prony method by suggesting to use robust covariance matrix for the identification of low frequency power system modes utilising the real time data obtained from phasor measurement unit. The methods reported in the current literature are many based on l(2)-norm minimisation, the estimated modes from these methods are severely affected in the presence of an outlier or bad measurements. Hence, there is a need to develop the method which can provide a good estimate of the modes even in the presence of outliers in the measurements. In order to mitigate the effect of such bad data, this study proposes a robust Prony estimator for estimating the low frequency modes of power systems. The method is based on minimum covariance determinant technique to find the robust covariance followed by improved Prony to estimate the modes. In this study the proposed method is compared with other methods such as improved Prony, etc. on synthetic test signal at different signal-to-noise ratio in the presence of outliers. Furthermore, the effectiveness of the proposed method is also shown on two area system and real time probing data of the Western Electricity Coordinating Council network.