基于卡尔曼滤波的风机控制系统优化

为进一步优化风机控制效果,缓解输入信号滞后于风能变化问题;在原有的控制算法基础上,引入卡尔曼滤波预测控制算法。建立了传动系统柔性模型,推导了卡尔曼滤波系统更新方程,并根据卡尔曼滤波原理研究了相关协方差确定方法,得到了滤波系数回归更新方法。利用系统平台和bladed软件进行仿真,证明了算法对传动振动优化效果和对功率曲线平稳性优化效果。结果表明,算法具有减缓传动链振动和平滑功率曲线的作用,可以在风场推广应用。

Optimization of the Wind Turbine Control System Based on Kalman Filtering

In order to optimize the control effect of the wind turbine and alleviate the problem of input signal lagging behind wind energy change, we have introduced Kalman filtering prediction control algorithm to the existing control algorithm, established a flexible model of the transmission system, derived the renewal equation for the Kalman filtering system, studied the method for determining related covariance in the principle of Kalman filtering, and obtained the method for updating the regression of the filter coefficient. Simulation is performed by using the system platform and bladed software. It is proved that the algorithm can optimize transmission vibration and power curve stability. The results show that this algorithm can reduce the vibration of the transmission chain and smooth the power curve, and can be applied to wind fields.