Soft sensor based on support vector machine for effective wind speed in large variable wind

Accurate estimation of wind speed can improve control capabilities of wind turbines. The wind speed is generally different at every point on the surface covered by the blades due to three dimensional and time-varied wind fields; effective wind speed cannot be measured by an anemometer. In this paper the problem of effective wind speed estimation is considered as soft sensor. Soft sensor modeling utilizes technique of support vector machine, which is efficient for the problem characterized by small sample, nonlinearity, high dimension, local minima and has high generalization. Comparing with Kalman filter, simulation results show support vector machine is an effective method for soft sensor modeling. Effective wind speed estimation can exactly track the trend of wind speed and has high estimation precision.