An adaptive neural PLL for grid synchronization

Abstract

In this paper, a new adaptive neural phase-locked loop (AN-PLL) based on adaptive linear neuron networks for grid-connected converters synchronization is presented. The proposed AN-PLL architecture contains three stages. Firstly, the frequency of polluted and distorted grid voltage is tracked online. Then, the grid-voltages are filtered as well as the voltage vector amplitude is detected. Finally, the phase angle is estimated by means of PLL. The whole AN-PLL architecture is implemented under dSPACE DS1104 and applied to a real three phase power supply. The performances and the robustness of the proposed AN-PLL under voltage sag and two-phase fault are compared to the conventional PLL. The obtained experimental results demonstrate that the proposed architecture presents overwhelming advantages in terms of tracking accuracy and immunity to grid-voltage disturbances.