Performance Enhancement of a Grid Connected Wind Turbine-Based PMSG Using Effective Predictive Control Algorithm

The paper introduces a study in which an effective control method is designed to enhance the dynamic performance of a wind driven permanent magnet synchronous generator (PMSG) connected to the utility grid. The proposed control method is formulated based on the predictive control and backstepping theories taking the advantages that these theories provide. The system components under consideration are modeled and described in details. The theoretical analysis of the proposed control is presented and described in a systematic approach. In order to evaluate the performance of the proposed predictive controller, a comprehensive comparative analysis is performed between four control techniques and the proposed one. The four control techniques are the vector control, predictive current control, predictive voltage based on PI and predictive voltage based on deadbeat theory. The captured results show that the generator's dynamics are improved significantly with the proposed controller through maintaining reduced ripples and current harmonics, faster dynamics and reduced computational burden as well. The captured results also confirm that the proposed controller outperforms predictive controllers that stand on a similar operating principle (i.e. predictive voltage control), which provides better performance for the wind turbine based generation system.