基于神经网络的直驱式风力发电最大风能控制研究

Research on Control Strategy of Maximum Wind Energy Capture of Direct-drive Wind Turbine Generator Based on Neural-network

在风力发电系统中,由于风轮处于三维时变的风场环境中,风速在整个风轮旋转平面上分布不同,风速计测量得到的风速和风轮旋转平面所受到的有效风速有很大差别。因此,该文提出基于神经网络的风速预测方法,该方法结合发电机转速预测模型应用于直驱式风力发电控制系统,进行最大风能追踪控制。仿真结果表明了该方法的正确性和可行性。

In the wind power system, due to the rotor of wind field on 3d time-varying environment, wind in the rotor spinning plane distribution is different, the velocity measured by the anemometer is different from the effective speed received on the wind turbine rotating flat. Therefore, this paper presents the neural- network-based prediction method, which was used to the directly driven wind energy system to capture the maximum wind energy combined with toter speed prediction. System simulation results have confirmed the functionality and performance of this method.