并网风力机中基于变桨距角的神经网络控制方法

Neural Network Control for Variable Pitch Angle in Grid Connected Wind Turbine

针对并网风力机的运行特性,在其传动系统和发电机的动态模型基础上设计控制器.当外界风速较大,提出采用基于神经网络的风力机叶片桨距角控制器抑制多余的风能进入发电系统,维持风力发电机馈送到电网的功率稳定;当风速较低时,风力机转速需要跟随风速变化,调整叶片桨距角处于捕捉最大风能位置处,保证风力机的风能转换效率最优,提高其运行效率.仿真结果验证了该控制方法的有效性.

For the operation characteristics of a grid connected wind turbine,two controllers are designed based on the dynamical model of the wind turbine drive system and generator.When the wind speed is higher,the neural network controller of the turbine blades pitch angle is proposed to restrict the excess wind energy entering the generation system in order to keep the power injected into the grid stable.Meanwhile,when the wind speed is lower,the turbine speed is changed with the variation of wind speed by adjusting the blades angle at the value of capturing maximum wind power,then the optimal wind energy conversion efficiency is guaranteed.The simulation results verify this control method is highly effective.