Dynamic Phasor Estimation Through DSTKF Under Transient Conditions

Abstract

This paper presents a double suboptimal-scaling-factor adaptive strong tracking Kalman filter (DSTKF)-based phasor measurement unit algorithm which can meet the accuracy requirement of the IEEE standard C37.118.1 under the dynamic condition. This method uses a $k$ th Taylor polynomial to linearize the complex exponential of the signal model, and estimates the dynamic phasor using DSTKF. The antialias filter unit for DSTKF algorithm is included to suppress high-order harmonics which will augment computing burden. By applying double suboptimal-scaling factors, DSTKF adjusts the process noise covariance matrix and the prediction covariance matrix in real time. Thereafter, amplitude and frequency measurement performances under various dynamic conditions are assessed in detail. Theoretical analysis and comprehensive experimental results validate the effectiveness of the proposed method.