TY - JOUR
T1 - A Fast and Precise Grid Synchronization Method Based on Fixed-Gain Filter
AU - Cai, Xinbo
AU - Wang, Can
AU - Kennel, Ralph
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2018/9
Y1 - 2018/9
N2 - 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.
AB - 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.
KW - Fixed-gain filter (FGF)
KW - Kalman filter (KF)
KW - phase-locked loop (PLL)
KW - state estimation
KW - synchronization
KW - three-phase grid
UR - http://www.scopus.com/inward/record.url?scp=85041294000&partnerID=8YFLogxK
U2 - 10.1109/TIE.2018.2798600
DO - 10.1109/TIE.2018.2798600
M3 - Article
AN - SCOPUS:85041294000
SN - 0278-0046
VL - 65
SP - 7119
EP - 7128
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 9
ER -