Instantaneous Oscillating Phasor Estimates With Taylor$^K$-Kalman Filters

Abstract

The state-transition matrix of the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> th order Taylor approximation to the dynamic phasor and its first derivatives leads to a plurality of state-space representations to approach the bandpass signal model of a power oscillation. With these truncated signal models, the Kalman filter algorithm can be applied to their state vectors in order to find observers able to estimate the dynamic phasor and its first derivatives. The estimates obtained through this technique, from oscillatory signals, are not only instantaneous (no delay) but also synchronous, an important attribute for control applications. They also provide frequency estimates. The new filters reduce the total vector error achieved with the traditional Kalman filter; are much more stable, with settling times five times lower; and improve the phasor estimates of oscillations with frequency offset.