Accurate Kalman filter based estimation of transmission line parameters utilizing synchronized phasor measurements

Abstract

Transmission line parameters are needed to be precisely known to ensure accurate power system analyses. In spite of various noise reduction methods, measurement noise can still affect the phasor measurement unit (PMU) data, leading to errors in the estimated parameters. A Kalman filter can be used to estimate these parameters from PMUs data which may suffer from noise. The existing methods often ignore the presence of noise in voltage measurements and therefore are vulnerable to errors when noise is presented in voltage measurements. In this paper, a new method that considers the noise in both voltage and current synchrophasors is introduced. A novel formulation for considering the voltage measurement noise is introduced when estimating transmission line parameters from PMU data. Consequently, an analytic derivation of the measurement noise covariance matrix for the Kalman filter is presented. Extensive simulation results demonstrate that compared to the existing methods, the developed formulation and the associated measurement covariance matrix significantly improve the accuracy of estimates.