Efficient real-time estimation for DFIG—Performance and reliability enhancement of grid/micro-grid connected energy conversion systems

This paper deals with an efficient real-time estimation (ERES) method for Doubly Fed Induction Generator (DFIG) parameters like resistances and inductances. The developed estimation technique is a sensorless method and is robust regarding measurement noises. Moreover, it estimates the rotating speed and the fluxes and their dynamics. The proposed estimation technique can easily serve to enhance the performances and the robustness of the related controllers. This technique can be employed for grid/micro-grid connected generation systems like DFIG-based Wind Energy Conversion Systems (WECSs) or other Energy Conversion Systems (ENCSs). The new approach is developed based on a DFIG state-space model and the recursive least squares algorithm. Simulations verify the viability of the proposed approach for a 1.5 MW DFIG-based WECS in the presence of measurement noises and parameter variations. A comparative study is also provided to show the superiority of the ERES-based adaptive sensorless sliding mode control approach compared to the classical one. It is observed that the motor drive ensures driving with a reduced number of sensors, lower tracking errors, and lower number of voltage fluctuations in the rotor.

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