MPPT and Pitch Angle Based on Neural Network Control of Wind Turbine Equipped with DFIG for All Operating Wind Speed Regions

2021 ◽  
pp. 1421-1432
Author(s):  
Moussa Reddak ◽  
Ayoub Nouaiti ◽  
Anass Gourma ◽  
Abdelmajid Berdai
Keyword(s):  
Neural Network ◽  
Wind Speed ◽  
Wind Turbine ◽  
Pitch Angle ◽  
Network Control ◽  
Neural Network Control

The Simulation of Pitch Control System for Variable Speed Wind Turbine Based on Neural Network

2011 ◽  
Vol 383-390 ◽  
pp. 2501-2506
Author(s):  
Li Na Liu ◽  
Hui Juan Qi ◽  
Bin Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Wind Speed ◽  
Wind Turbine ◽  
Output Power ◽  
Pitch Angle ◽  
Optimal Control Strategy ◽  
Pitch Control ◽  
Detailed Simulation ◽  
And Performance

The parameters of large wind turbine need to be adjusted timely to avoid excessive wind energy that will cause damage on the wind turbine itself. Based on the simplified mathematical model of wind turbine, we got the relationship curve between its parameters. When the speed of wind was higher than the rated wind speed, we figure out the value of pitch angle during the changes of effective wind speed to keep rated output power. Neural Network used to train the data and pitch control system was built, it used to adjust pitch angle once the wind changes, and maintain the output power at rated value. The complex mathematical relation can be replaced by the trained network model. Detailed simulation results have confirmed the feasibility and performance of the optimal control strategy, which protect the wind turbine from damage and prolong its service life.

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