State Estimation MRAS and Identification of Stator Winding Phase Fault Detection of the PMSG in Wind Energy Based on the Sliding Mode Control
			
	
 
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				1
				Higher National School of Renewable Energy, Environment and Sustainable Development, LSPIE Laboratory, Batna, Algeria
				 
			 
						
				2
				Laboratory of Innovative Technologies, COSI Team, ENST, Algiers, Algeria
				 
			 
						
				3
				Laboratory LTI, University of Picardie Jules Verne, Cuffies, Soissons, France
				 
			 
										
				
				
		
		 
			
			
		
		
		
		
		
		
	
							
										    		
    			 
    			
    				    					Corresponding author
    					    				    				
    					Samir  Meradi   
    					Laboratory of Innovative Technologies, COSI Team, ENST  Algiers –Algeria
    				
 
    			
				 
    			 
    		 		
			
																						 
		
	 
		
 
 
Power Electronics and Drives 2023;8 (43):109-127
		
 
 
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ABSTRACT
This paper proposes a method for the diagnosis of stator inter-turn short-circuit fault for permanent magnet synchronous generators
(PMSG). Inter-turn short-circuit currents are among the most critical in PMSG. For safety considerations, a fast detection is required
when a fault occurs. This approach uses the parameter estimation of the per-phase stator resistance in closed-loop control of variable
speed of wind energy conversion system (WECS). In the presence of an incipient short-circuit fault, the estimation of the resistance
of the stator in the d-q reference frame does not make it possible to give the exact information. To solve this problem, a novel fault
diagnosis scheme is proposed using parameter estimation of the per-phase stator resistance. The per-phase stator resistance of
PMSG is estimated using the MRAS algorithm technique in real time. Based on a faulty PMSG model expressed in Park’s reference
frame, the number of short-circuited turns is estimated using MRAS. Fault diagnosis is on line detected by analysing the estimated
stator resistance of each phase according to the fault condition. The proposed fault diagnosis scheme is implemented without any
extra devices. Moreover, the information on the estimated parameters can be used to improve the control performance. The simulation
results demonstrate that the proposed method can estimate the faulty phase.