A Fast and Precise Grid Synchronization Method Based on Fixed-Gain Filter

As the demand for electricity is growing and the penetration of renewable energy resources is increasing, grid synchronization with high accuracy is essential for utility networks. This paper presents a novel fixed-gain filter (FGF) scheme with an optimal fixed feedback gain matrix to estimate the (angle) position and frequency of the grid, which ensures a fast and accurate synchronization under varying grid conditions. Instead of using the conventional phase-locked loop (PLL) scheme that suffers from the difficulty of parameter selection, the concept of the Kalman filter (KF) is synthesized to design the second-order FGF and third-order FGF for synchronization. To overcome the heavy computational processing for the KF, the feedback gain is subject to a single tunable parameter only, which can be calculated offline and refined within a certain small range fulfilling the system stability criterion. Compared with the PLL approach, the new FGF provides a faster and more precise tracking performance, an easier parameter tuning mechanism, a lower program complexity, and a better grid stability, which is verified by simulations and experiments in all cases.     «

As the demand for electricity is growing and the penetration of renewable energy resources is increasing, grid synchronization with high accuracy is essential for utility networks. This paper presents a novel fixed-gain filter (FGF) scheme with an optimal fixed feedback gain matrix to estimate the (angle) position and frequency of the grid, which ensures a fast and accurate synchronization under varying grid conditions. Instead of using the conventional phase-locked loop (PLL) scheme that suffer...     »