Wind Speed Estimation Algorithm in the Presence of Observation Noise

Abstract

A stochastic hub-height wind speed estimation algorithm for wind turbines, which requires only the rotor angular velocity measurement in the presence of observation noise is proposed. It is assumed that the power curve and the total inertia of the rotor are known a priori. We use the maximum likelihood estimator to identify the hub-height wind speed, which is formulated as one of the state variables in the nonlinear model. The theory and algorithm are verified by both simulated and experimental data in the presence of measurement noise. The effects of the initial guess, the noise variance, and the time history are discussed.