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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We consider the impulse surge voltages acting on alternators running in thc block with the elevating transformer. The alternators' insulations are not stable, particularly when being in the block alternators are placed in more severe conditions because the surge voltage waves coming from the line and through the step-up transformer have a direct effect on them. It is interesting to know whether the limitation of the surge voltage waves at the input of the HV winding of the transformer, by mean of lightning arresters is sufficient to protect the alternators' insulation. According to thc collccted results wc observc that this limitation is not efficient in the case of alternators and that it is iinportant to connect lightning arresters across the LV winding.