Title :
The Estimation of Wind Turbine Pitch Angle Based on ANN
Author :
Liu, Yanping ; Liu, Shuhong ; Guo, Hongmei ; Wang, Huajun
Author_Institution :
Inst. of Inf. Eng., Hebei Univ. of Technol., Tianjin, China
Abstract :
Variable-speed and constant-frequency (VSCF) pitch-controlled wind turbine is believed to be superior to other types of wind turbine due to its features such as high efficiency and ideal starting and braking performance, artificial neural networks (ANN) technology is adopted to predict pitch angle at real-time working condition, and to obtain more accurate pitch angle reference value. It enhances control precision of the entire pitch-controlled system. Pitch-controlled system, the very core of a large-scale wind turbine control system, is playing a very important role in the security, stability and efficient operation of the units.
Keywords :
neurocontrollers; power generation control; wind turbines; ANN; artificial neural networks; real-time working condition; starting-braking performance; variable-speed and constant-frequency pitch-controlled wind turbine; wind turbine pitch angle estimation; Artificial neural networks; Control systems; Mathematical model; Neural networks; Power generation; Rotors; Wind energy; Wind energy generation; Wind speed; Wind turbines; ANN; Pitch-controlled system; VSCF; pitch angle;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
DOI :
10.1109/ICINIS.2009.153