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A wind speed estimation method using adaptive Kalman filtering for a variable speed stall regulated wind turbine

机译:基于自适应卡尔曼滤波的变速失速调节风轮机风速估计方法

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This paper presents a method for the estimation of the effective wind speed acting on the rotor of a wind turbine in order to be used for the control of a variable speed stall regulated wind turbine. The estimation algorithm consists of a Kalman filter, estimating the aerodynamic torque acting on the rotor of the turbine, and a Newton-Raphson method, which derives the effective wind speed from the aerodynamic torque. The Kalman filter is enhanced with adaptive algorithms that estimate the unknown covariances of the measurement and process noise respectively, keeping the filter continuously tuned close to its optimal behavior. The presented algorithm and results are based on a full model of a wind turbine, which entails the presence of two flexible shafts and three moments of inertia. From software and hardware simulation results it can be seen that the method is quite promising.
机译:本文提出了一种估算作用在风力涡轮机转子上的有效风速的方法,以用于控制变速失速调节的风力涡轮机。估算算法包括一个卡尔曼滤波器(估算作用在涡轮机转子上的空气动力扭矩)和牛顿-拉夫森方法,该方法从空气动力扭矩中得出有效风速。卡尔曼滤波器通过自适应算法进行了增强,自适应算法分别估计测量和过程噪声的未知协方差,从而使滤波器连续不断地调谐至接近其最佳性能。提出的算法和结果基于风力涡轮机的完整模型,该模型需要存在两个柔性轴和三个惯性矩。从软件和硬件仿真结果可以看出,该方法很有前途。

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