A neural network based wind speed estimator for a wind turbine control

Variable speed wind generation systems are more attractive than fixed-speed systems because of the more efficient energy production improved power quality, and improved dynamic performance during grid disturbances. In this sense, to implement maximum wind power extraction, most controller designs of the variable-speed wind turbine generators employ anemometers to measure wind speed in order to derive the desired optimal shaft speed for adjusting the generator speed. In this paper it is proposed a new Neural Network Based Wind Speed Estimator for a wind turbine control. The design uses an feedforward Artificial Neural Network (ANN) to implement a rotor speed estimator, and simulated results show that the proposed observer provides high-performance dynamic characteristics.