Optimization
Ehsanolah Assareh; Iman Poultangari; Afshin Ghanbarzadeh
Abstract
With pitch angle control, wind turbines can retain power generated at high speeds of wind and avoid severe mechanical stress. By varying the angle of the blades of the wind turbines, they can keep the power generated up near the maximum amount. A controller based on PI is suggested due to control angle ...
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With pitch angle control, wind turbines can retain power generated at high speeds of wind and avoid severe mechanical stress. By varying the angle of the blades of the wind turbines, they can keep the power generated up near the maximum amount. A controller based on PI is suggested due to control angle of the pitch of the wind turbine blades in the present study. Therefore, PI controller gains are tuned via hybridization of firefly evolutionary algorithm and MLP artificial neural network so that the controller at its output sends a suitable control signal to the pitch actuator and thus varies the blades pitch angle appropriately to preserve power of the generator at a nominal amount even at high wind speeds. Simulating and analyzing the results was done by employing a five MW wind turbine made by National Renewable Energy Laboratory based on FAST software code. The simulation of the method showed that its performance is good.
