A new improved control for power quality enhancement in double fed induction generator using iterative learning control
 
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Laboratoire de Génie Electrique, Department of Electrical Engineering, Faculty of Technology, University Mohamed Boudiaf of M’Sila, Algeria
 
2
Laboratoire de Génie Electrique, Department of Electrical Engineering, University of M’Sila, Algeria
 
 
Submission date: 2023-03-07
 
 
Final revision date: 2023-07-02
 
 
Acceptance date: 2023-07-10
 
 
Online publication date: 2023-08-21
 
 
Publication date: 2023-08-21
 
 
Corresponding author
Ooussama Djaidja   

Laboratoire de Génie Electrique, Department of Electrical Engineering, Faculty of Technology, University Mohamed Boudiaf of M’Sila, Algeria
 
 
Diagnostyka 2023;24(3):2023309
 
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ABSTRACT
This work presents a new fault-tolerant control approach for a doubly fed induction generator using iterative learning control when the fault occurs. The goal of this research is to apply the proposed ILC controller in conjunction with vector control for doubly fed induction generator to enhance its reliability and availability under broken rotor bars (BRB). However, the performances of classical VC control are often characterized by their inability to deal with the effects of faults. To overcome these drawbacks, a combination of VC control and iterative learning control is described. The input control signal of the VC controller is gradually regulated by the ILC harmonic compensator in order to eliminate the faults effect. The improvement of this approach related to active and reactive power ripples overshoot and response time have been explained. Which active and reactive power response time have been reduced more than 84% and 87.5 % respectively. The active and reactive power overshoots have been reduced about 45% and 35% respectively. The obtained results emphasize the efficiency and the ability of the proposed FTC to enhance the power quality in faulty condition
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