Adaptive neural PLL for grid-connected DFIG synchronization

A Bechouche, DO Abdeslam… - Journal of Power …, 2014 - koreascience.kr
Journal of Power Electronics, 2014koreascience.kr
In this paper, an adaptive neural phase-locked loop (AN-PLL) based on adaptive linear
neuron is proposed for grid-connected doubly fed induction generator (DFIG)
synchronization. The proposed AN-PLL architecture comprises three stages, namely, the
frequency of polluted and distorted grid voltages is tracked online; the grid voltages are
filtered, and the voltage vector amplitude is detected; the phase angle is estimated. First, the
AN-PLL architecture is implemented and applied to a real three-phase power supply …
Abstract
In this paper, an adaptive neural phase-locked loop (AN-PLL) based on adaptive linear neuron is proposed for grid-connected doubly fed induction generator (DFIG) synchronization. The proposed AN-PLL architecture comprises three stages, namely, the frequency of polluted and distorted grid voltages is tracked online; the grid voltages are filtered, and the voltage vector amplitude is detected; the phase angle is estimated. First, the AN-PLL architecture is implemented and applied to a real three-phase power supply. Thereafter, the performances and robustness of the new AN-PLL under voltage sag and two-phase faults are compared with those of conventional PLL. Finally, an application of the suggested AN-PLL in the grid-connected DFIG-decoupled control strategy is conducted. Experimental results prove the good performances of the new AN-PLL in grid-connected DFIG synchronization.
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