Title :
Application of Neural Network Technology in the Individual Pitch Control System
Author :
Wang Shouyi ; Xing Gang
Author_Institution :
Sch. of Electr. Eng. & Autom., Tianjin Polytech. Univ., Tianjin, China
Abstract :
Owing to the lower energy density, the randomness and the instability of the wind energy, it is difficult to control the large-scale wind turbine generators. Based on the domestic megawatt wind turbine generator system, the pitch control techniques for large scale wind turbine are deeply analyzed in this thesis. The basic law of pitch control is analyzed on the basis of the theory of wind turbine blade aerodynamics, and then a design of individual pitch control is proposed. By the use of neural networks, a new strategy of control individual pitch control (IPC) which is based on inflow angle prediction is put forward. By means of simulation results, it can be concluded that IPC can effectively reduce the aerodynamic fatigue load on blades, and the result of power control is prefect.
Keywords :
aerodynamics; blades; neurocontrollers; power control; power generation control; wind power; wind turbines; aerodynamic fatigue load; domestic megawatt wind turbine generator system; individual pitch control system; inflow angle prediction; neural network technology; power control; wind energy; wind turbine blade aerodynamics; wind turbine generator control; Aerodynamics; Blades; Force; Generators; Rotors; Wind speed; Wind turbines;
Conference_Titel :
Control, Automation and Systems Engineering (CASE), 2011 International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4577-0859-6
DOI :
10.1109/ICCASE.2011.5997550