Determination of steady state control laws of doubly - fed induction generator using natural and power variables

Author(s):  
Adeola Balogun ◽  
Olorunfemi Ojo ◽  
Frank Okafor ◽  
Sosthenes Karugaba
IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 9479-9488 ◽  
Author(s):  
Yuntao Ju ◽  
Fuchao Ge ◽  
Wenchuan Wu ◽  
Yi Lin ◽  
Jing Wang

Author(s):  
Sukhwinder Singh Dhillon ◽  
Jagdeep Singh Lather ◽  
Sanjay Marwaha

This paper present steady state and dynamic (Transient) models of the doubly fed induction generator connected to grid. The steady state model of the DFIAG (Doubly Fed Asynchronous induction Generator) has been constructed by referring all the rotor quantities to stator side. With the help of MATLAB programming simulation results are obtained to depict the steady state response of electromechanical torque, rotor speed, stator and rotor currents, stator and rotor fluxes, active and reactive drawn and delivered by Doubly fed Asynchronous Induction machine (DFAIM) as it is operating in two modes i.e. generator and motor. The mathematical steady state and transient model of the DFIAM is constructed for three basic reference frames such as rotor, stator and synchronously revolving reference frame using first order deferential equations. The effect of unsaturated and saturated resultant flux on the mutual inductance is also taken into account to deeply understand the dynamic response of the machine. The steady state and dynamic response of the DFAIG are compared for different rotor voltage magnitudes. Also, the effect of variations in mechanical input torque, stator voltage variations are simulated to predict the stator and rotor currents, active and reactive power, electromagnetic torque and rotor speed variations.


Author(s):  
Fouad Abdelmalki ◽  
Najat Ouaaline

This paper aims to ensure a stability and observability of doubly fed induction generator DFIG of a wind turbine based on the approach of fuzzy control type T-S PDC (Parallel Distributed Compensation) which determines the control laws by return state and fuzzy observers. First, the fuzzy TS model is used to precisely represent a nonlinear model of DFIG proposed and adopted in this work. Then, the stability analysis is based on the quadratic Lyapunov function to determine the gains that ensure the stability conditions. The fuzzy observer of DFIG is built to estimate non-measurable state vectors and the estimated states converging to the actual statements. The gains of observatory and of stability are obtained by solving a set of linear matrix inequality (LMI). Finally, numerical simulations are performed to verify the theoretical results and demonstrate satisfactory performance.


2011 ◽  
Vol 03 (04) ◽  
pp. 393-400 ◽  
Author(s):  
Ahmad M. Alkandari ◽  
S. A. Soliman ◽  
Mansour H. Abdel-Rahman

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