Title :
State estimation of DFIG using an Extended Kalman Filter with an augmented state model
Author :
Malakar, Mridul Kanti ; Tripathy, Praveen ; Krishnaswamy, Srinivasan
Author_Institution :
Dept. of Electron. & Electr. Eng., Indian Inst. of Technol., Guwahati, Guwahati, India
Abstract :
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.
Keywords :
Kalman filters; asynchronous generators; rotors; state estimation; DFIG; MATLAB; Simulink; augmented state model; doubly fed induction generators; extended Kalman filter; nonlinear state space model; rotor position; speed estimates; state estimation; Induction generators; Kalman filters; Mathematical model; Rotors; Stators; Torque; Wind turbines; Doubly fed induction generator; Extended Kalman Filter; rotor position and speed estimation;
Conference_Titel :
Power Systems Conference (NPSC), 2014 Eighteenth National
DOI :
10.1109/NPSC.2014.7103891
