A genetic algorithm is proposed to optimize the yaw control system used for the stable and efficient operation of turbines in wind power plants. In particular, the factors that produce yaw static deviation are analyzed. Then, the sought optimization method for the yaw static deviation of the wind turbine is implemented by using a lidar wind meter in the engine room in order to solve the low accuracy problem caused by yaw static deviation. It is shown that fuzzy control can overcome problematic factors such as the randomness of wind direction and track the change of wind direction accurately. Power control implementation is simple, as only the voltage and current of the generator need to be measured.
Cite This Article
APA Style
Shang, L., Jia, Y., Zheng, L., Shi, E., Sun, M. (2022). A genetic algorithm for optimizing yaw operation control in wind power plants. Fluid Dynamics & Materials Processing, 18(3), 511-519. https://doi.org/10.32604/fdmp.2022.017920
Vancouver Style
Shang L, Jia Y, Zheng L, Shi E, Sun M. A genetic algorithm for optimizing yaw operation control in wind power plants. Fluid Dyn Mater Proc. 2022;18(3):511-519 https://doi.org/10.32604/fdmp.2022.017920
IEEE Style
L. Shang, Y. Jia, L. Zheng, E. Shi, and M. Sun "A Genetic Algorithm for Optimizing Yaw Operation Control in Wind Power Plants," Fluid Dyn. Mater. Proc., vol. 18, no. 3, pp. 511-519. 2022. https://doi.org/10.32604/fdmp.2022.017920