  This paper proposes a decentralized dynamic state estimation scheme for
microgrids. The approach employs the voltage and current measurements in the
dq0 reference frame through phasor synchronization to be able to exclude
orthogonal functions from their relationship formulas. Based on that premise,
we utilize a Kalman filter to dynamically estimate states of microgrids. The
decoupling of measurement values to state and input vectors reduces the
computational complexity. The Kalman filter considers the process noise
covariances, which are modified with respect to the covariance of measured
input values. Theoretical analysis and simulation results are provided for
validation.
