Widely linear state space models for frequency estimation in unbalanced three-phase systems

Abstract

A novel technique for the online frequency estimation of three-phase power systems using the widely linear (augmented) complex least mean square (ACLMS) algorithm has recently been proposed, and was shown to achieve significantly better estimates than conventional complex least mean square (CLMS) algorithm based frequency estimation under unbalanced system conditions. In this paper, we consider the frequency estimation problem from the state space point of view, and show that the augmented complex Kalman filter (ACKF) offers significantly better performance than ACLMS.