Speed-sensorless vector control of an wind turbine induction generator using artificial neural network

This paper present speed-sensorless vector control strategy for a squirrel cage induction generator (SCIG) used in variable speed wind energy conversion systems (WECS). In order to perform maximum power point tracking control (MPPT) of WECS, it is necessary to drive wind turbine at an optimal rotor speed. In this paper, rotational speed of the SCIG is estimated using improved model reference adaptive system (MRAS observer), with adaptive model based on artificial neural network (ANN). Extensive experimentation is conducted in order to verify efficiency and reliability of proposed control technique.