Browse by author
Lookup NU author(s): Dr Juchuan Dai,
Dr Wenxian YangORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Active wake management (AWM) via yaw control has been discussed in recent years as a potential way to improve the power production of a wind farm. In such a technique, the wind turbines will be required to work frequently at misaligned yaw angles in order to reduce the vortices in the wake area behind the turbines. However, today, it is still not very clear about how yaw operation affects the dynamics and power generation performance of the wind turbines. To further understand the effects of yaw operation, numerical research is conducted in this paper. In the study, the optimal size of the flow field used in the computational fluid dynamics (CFD) calculation was specifically discussed in order to obtain an efficient numerical model to quickly and accurately predict the dynamics and the performance of the turbines. Through this research, the correlation between the blade loads during yaw and non-yaw operations is established for aiding yaw control, and the blade loads and power generation performances of the wind turbine during yaw operation under different wind shear and blade deflection conditions are analyzed for understanding the effects of yaw operation. It is found that the optimal size of the flow field for performing efficient and accurate CFD calculations does exist. The misaligned yaw operation generally tends to decrease the loads acting on the blade. However, the aerodynamic energy captured by the turbine rotor and blade loads during yaw operation is not only dependent on the yaw angle of the rotor but is also affected by wind speed, rotor speed, the pitch angle of the blades, blade deflection, and wind shear. Particularly, it is interestingly found that wind shear can cause undesirable fluctuation of the power, which will challenge the power quality of the wind farm if no measures are taken.
Author(s): Dai J, Yang X, Yang W, Gao G, Li M
Publication type: Article
Publication status: Published
Journal: Applied Sciences
Online publication date: 13/03/2020
Acceptance date: 10/03/2020
Date deposited: 16/03/2020
ISSN (electronic): 2076-3417
Publisher: MDPI AG
Altmetrics provided by Altmetric