A Virtual-Flux State Observer-Based Inductance Identification Method for Model Predictive Control of Grid-Tied Inverters With a Finite Phase Angle Set-Based PLL
Leilei Guo, Han Xiao, Hailiang Zhao, Zhiyan Zhang, Changzhou Yu, Xiaoliang Yang, Hong Zhu
Abstract
To reduce the calculation burden of the conventional finite phase angle set-based phase-locked loop (PLL) and enhance the parameter robustness of the model predictive control for grid-tied inverters, an improved finite phase angle set-based PLL and a new inductance identification method based on virtual-flux state observer (VFSO) are proposed in this article. First, three improved PLLs are proposed based on the principles of the conventional finite phase angle set-based PLL. Second, the proposed PLLs are further improved by redesigning the cost function, which can search the optimal phase angle within the region of [0, π] instead of [0, 2π], reducing the iteration times. Third, a new VFSO with only one observer parameter is proposed, based on which a new inductance identification method is presented. Fourth, by analyzing the characteristics of the proposed VFSO, it is found that a larger observer gain can improve the dynamic convergence speed of the proposed VFSO, while a smaller one can enhance its robustness against grid frequency deviation. So, an observer gain adaptive method is proposed, aiming to improve both the dynamic and steady-state control performance of the proposed inductance identification method. Finally, comparative experimental studies verify the effectiveness of the proposed strategies.