The present paper aims to introduce an effective control system which enhances the dynamics of a doubly fed induction generator (DFIG) operating at fixed and variable speeds. To visualize the effectiveness of the formulated control algorithm, the performance of the DFIG is evaluated using other control techniques as well. Each control algorithm is primarily described by showing its operation principles and how it is adapted to manage the DFIG’s operation. The main used control strategies are stator voltage-oriented control (SVOC), model predictive current control (MPCC), model predictive direct torque control (MPDTC), and the formulated predictive voltage control (PVC) algorithm. A detailed comparison is performed between the controllers’ performances, through which the advantages and shortcomings of each method are outlined, and finally, the most effective technique is identified amongst them. The obtained results reveal that the proposed PVC approach possesses multiple advantages such as a faster dynamic response and simpler control structure when compared with SVOC and a faster dynamic response, reduced ripples, and reduced computational burdens when compared with the MPCC and MPDTC approaches. In addition, the robustness of the proposed PVC scheme is confirmed by performing extensive performance evaluation tests considering the parameters’ variation.

The article seeks to improve the dynamic performance of a standalone doubly fed induction generator (DFIG) which driven by a wind turbine, with the help of an effective control approach. The superiority of the designed predictive controller can be confirmed through evaluating the performance of the DFIG under other control algorithm, which is the model predictive direct torque control (MPDTC), model predictive current control (MPCC) as classic types of control. Firstly, the operating principles of the two controllers are described in details. After that, a comprehensive comparison is performed among the dynamic performances of the designed MPDTC, MPCC techniques and the predictive control strategy, so we can easily present the merits and deficiencies of each control scheme to be able to easily select the most appropriate algorithm to be utilized with the DFIG. The comparison is carried out in terms of system simplicity, dynamic response, ripples’ content, number of performed commutations and total harmonic distortion (THD). The results of the comparison prove the effectiveness and validation of our proposed predictive controller; as it achieves the system simplicity, its dynamic response is faster than that of MPDTC and MPCC, it presents a lower content of ripples compared to MPDTC and MPCC. Moreover, it can minimize the computational burden, remarkably. Furthermore, the numerical results are showing a marked reduction in the THD with a percentage of 2.23 % compared to MPDTC and 1.8 % compared to MPCC. For these reasons, it can be said that the formulated controller is the most convenient to be used with the DFIG to achieve the best dynamic performance.

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