A Bank of Kalman Filters for Current Sensors Faults Detection and Isolation of DFIG for Wind Turbine

Imane Idrissi (1) , Rachid El Bachtiri (1) , Houcine Chafouk (2)

1 USMBA - Université Sidi Mohamed Ben Abdellah
2 Pôle Automatique et Systèmes

This paper presents a model based Fault diagnosis approach. This approach is based on a bank of Kalman filters. These filters are structured according to the Dedicated Observer Scheme (DOS)., for detecting and isolating multiple and simultaneous current sensors faults of a doubly fed induction generator (DFIG) widely used in variable speed wind turbines. Then., a linear varying parameter model of DFIG is established and the faults diagnosis procedure is implemented. The DFIG model design and the model-based Fault Detection and Isolation (FDI) approach are performed in the Matlab/Simulink environment.

Domains: Engineering Sciences [physics]; Automatic

Imane Idrissi, Rachid El Bachtiri, Houcine Chafouk. A Bank of Kalman Filters for Current Sensors Faults Detection and Isolation of DFIG for Wind Turbine. 2017 International Renewable and Sustainable Energy Conference (IRSEC), Dec 2017, Tangier, Morocco. pp.1-6, ⟨10.1109/IRSEC.2017.8477263⟩. ⟨hal-02418856⟩