Bank of Extended Kalman Filters for Faults Diagnosis in Wind Turbine Doubly Fed Induction Generator

In order to increase the efficiency, to ensure availability and to prevent unexpected failures of thedoubly fed induction generator (DFIG), widely used in speed variable wind turbine (SVWT), a model basedapproach is proposed for diagnosing stator and rotor winding and current sensors faults in the generator.In this study, the Extended Kalman Filter (EKF) is used as state and parameter estimation method for thismodel based diagnosis approach. The generator windings faults and current instruments defects aremodelled, detected and isolated with the use of the faults indicators called residuals, which are obtainedbased on the EKF observer. The mathematical model of DFIG for both healthy and faulty operatingconditions is implemented in Matlab/Simulink software. The obtained simulation results demonstrate theeffectiveness of the proposed technique for diagnosis and quantification of the faults under study