This paper suggests a new fuzzy method for active power (AP) and reactive power (RP) control of a power grid that includes wind turbines and Doubly Fed Induction Generators (DFIGs). A Recurrent Type-II Fuzzy Neural Networks (RT2FNN) controller based on Radial Basis Function Networks (RBFN) is applied to the rotor side converter for the power control and voltage regulation of the wind turbine equipped with the DFIG. In order to train a model, the voltage profile at each bus, and the reactive power of the power grid are given to the RT2FNN as the input and output, respectively. A wind turbine and its control units are studied in detail. Simulation results, obtained in MATLAB software, show the well performance, robustness, good accuracy and power quality improvement of the suggested controller in the wind-driven DFIGs.

本文提出了一种新的模糊方法，用于对包括风力涡轮机和双馈感应发电机 (DFIG) 的电网进行有功功率 (AP) 和无功功率 (RP) 控制。基于径向基函数网络（RBFN）的递归II型模糊神经网络（RT2FNN）控制器应用于转子侧变流器，用于配备双馈电机的风力涡轮机的功率控制和电压调节。为了训练模型，每条母线的电压曲线和电网的无功功率分别作为输入和输出提供给 RT2FNN。详细研究了风力涡轮机及其控制单元。在 MATLAB 软件中获得的仿真结果表明，所建议的控制器在风力驱动的双馈发电机中具有良好的性能、鲁棒性、良好的精度和电能质量。