Application of Kalman filtering for online estimation of symmetrical components for power system protection

This paper presents a new model that enables linear Kalman filtering (KF) to be applied for the direct estimation of symmetrical components in unbalanced three-phase systems. Computational experiments implementing KF using both synthetic and actual data sets are reported. It is shown that Kalman filtering models are well suited for symmetrical component estimation online. The effects of sampling rate, data window size and frequency drift on the optimal estimates are also studied.