Dynamic evaluation of optimization techniques–based proportional–integral controller for wind-driven permanent magnet synchronous generator

Converters of permanent magnet synchronous generator (PMSG), driven by wind turbines, are controlled by a classical proportional–integral controller. However, many research studies highlighted the challenge in PMSG due to the poor performance of the classical proportional–integral controller, especially in the event of faults or wind speed variations. This article proposes a solution for the limitations of the classical proportional–integral controller with PMSG driven by a wind turbine. The proposed solution includes two optimization techniques: gray wolf optimizer and whale optimizer algorithm. To ensure the effectiveness of the proposed techniques, step change and random variation of wind speed are studied. Moreover, fault ride-through capability of the PMSG is studied with gray wolf optimizer and whale optimizer algorithm techniques during the occurrence of a three-phase fault incident. In this case, a braking chopper controlled by a hysteresis controller is connected to the DC-link capacitor. The simulated results show that compared with the classical proportional–integral controller, gray wolf optimizer and whale optimizer algorithm techniques are greatly efficient in improving the dynamic behavior of the PMSG during wind speed variations. Moreover, gray wolf optimizer and whale optimizer algorithm techniques present their effectiveness during the fault incident by suppressing the transient variations of all the PMSG parameters, improving the fault ride-through capability, and decreasing the total harmonic distortion of the current waveforms. All simulations are performed with MATLAB/ Simulink program package.