Application of Kalman Filter to Parameter Estimation of Doubly-Fed Induction Generators in Wind Turbine Systems

This paper presents deals with the analysis, modeling, and control of the doubly-fed induction generator (DFIG) for wind turbines. Different rotor current control methods are investigated with the objective of eliminating the influence of the back electromotive force (EMF(, on the rotor current. It is found that the method that utilizes both feed forward of the back EMF and so called “active resistance” manages best to suppress the influence of the back EMF on the rotor current of the investigated methods. This method also has the best stability properties. In addition it is found that this method also has the best robustness to parameter deviations. This paper presents a novel method for state estimation in doubly fed induction generators (DFIGs) using an Extended Kalman Filter. In this work, the conventional nonlinear state space model of a DFIG has been augmented with additional states in order to make rotor position and speed estimates more robust to disturbances. The effectiveness of this method has been tested for various transient cases using MATLAB/Simulink.