Particle Filter based Grid Synchronization with Voltage Unbalance and Frequency Variation in Smart Grid

Computing the phase angle of a three-phase voltage signal in utility grid is critical for the synchronization of smart grid. Only if the phase angle is accurately estimated, the energy transfer between the distributed power generators and the utility grid can be properly controlled. In this paper, we propose a particle filter (PF) based scheme to estimate the phase angle of the utility grid in the presence of voltage unbalance and frequency variation in the alpha beta stationary reference frame where the positive and negative sequences of the input three-phase signal are separated by Clarke transformation. For the filter algorithm, the traditional SIR filter is customized for the grid synchronization problem by exploiting the feature of the grid state system dynamics and incorporating the deterministic resampling. Extensive simulations have been conducted to verify the effectiveness and efficiency of the proposed PF-based synchronization scheme. It is shown that the proposed PF-based scheme outperforms the traditional EKF-based scheme in terms of both estimation accuracy and convergence time, when both the voltage imbalance and frequency variation are exerted.