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

This paper presents an effective control strategy is developed to enhance the dynamic performance of a wind-driven Permanent Magnet Synchronous Generator (PMSG) connected to the utility grid. The proposed method is formulated by integrating predictive control with backstepping theory, leveraging the strengths of both approaches. The system components are thoroughly modeled and described in detail. A systematic theoretical analysis of the proposed controller is provided. To evaluate its effectiveness, a comprehensive comparative study is conducted against four existing control techniques: vector control, predictive current control, predictive voltage control based on PI regulation, and predictive voltage control based on deadbeat theory. The simulation results demonstrate that the proposed controller pvc based backstepping significantly improves the generator's dynamic performance by reducing current ripples, minimizing harmonic distortion, accelerating dynamic response, and lowering computational complexity. Moreover, the results confirm that the proposed controller outperforms other predictive voltage control methods operating on similar principles, thereby offering superior performance for wind turbine-based power generation systems.by using matlab simulink software 2024a

Keywords: Wind turbine, Grid, PMSG, FOC, PI Controller, PWM.