Title :
SVR-based Wind Speed Estimation for Power Control of Wind Energy Generation System
Author :
Abo-Khalil, Ahmed G. ; Lee, Dong-Choon
Author_Institution :
Yeungnam Univ., Gyeongbuk
Abstract :
This paper presents a new wind speed estimation method for a variable speed wind turbine system, where the theory of SVR (support vector regression) is applied. The turbine speed is controlled to capture the maximum power according to the optimal tip-speed ratio. The inputs of SVR estimator are the wind turbine power and the rotational speed. By off-line training, a specified function which relates the input with the output is obtained. Then, the wind speed is determined from this predicted off-line function and the instantaneous input. The simulation and experimental results have shown that the wind speed is estimated rapidly and accurately.
Keywords :
power control; power generation control; regression analysis; wind turbines; SVR-based wind speed estimation; off-line training; power control; support vector regression; variable speed wind turbine system; wind energy generation system; Fluid flow measurement; Neural networks; Polynomials; Power control; Power generation; Velocity measurement; Wind energy; Wind energy generation; Wind speed; Wind turbines; SVR; Wind speed estimation; wind turbine;
Conference_Titel :
Power Conversion Conference - Nagoya, 2007. PCC '07
Conference_Location :
Nagoya
Print_ISBN :
1-4244-0844-X
Electronic_ISBN :
1-4244-0844-X
DOI :
10.1109/PCCON.2007.373152