Research on complex wake interference of aligned rotors considering the precone variation of the upstream wind turbine

• Published in: Frontiers in Marine Science Vol. 9
• Main Authors: Zhang, Yuquan, Ji, Renwei, Sun, Ke, Zhang, Zhi, Zheng, Yuan, Zhang, Jisheng, Zhang, Xuewei, Rodriguez, Emmanuel Fernandez
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 06.12.2022
• Subjects: actuator line; large eddy simulation; precone variation; refined numerical simulation; vortex identification method; wind turbine
• ISSN: 2296-7745; 2296-7745
• DOI: 10.3389/fmars.2022.1039233

To understand the interaction wake effects of aligned horizontal-axis wind turbines, a refined and low-cost wake simulation framework is developed by combining the actuator line (AL) with a local dynamic Smagorinsky (LDS) model. Firstly, the published performance of the NREL-5MW wind turbine is used to corroborate the accuracy of the AL-LDS coupling model. Secondly, the research is extended to predict the interference between two tandem rotor wakes. The influence of the precone characteristics on the overall wake and power output of the tandem wind turbines is explored by modifying the upstream wind turbine and introducing the latest third-generation Ω vortex identification method in the post-processing procedure. According to results, the tandem wind turbines have complex wake interference, with the precone angle variation always reducing the global output power, and leading to an unstable downstream turbine wake. This is detrimental to system lifespan due to high performance fluctuation and stress and as well may have ecological implications due to sediment alteration. From results, an upwind turbine with precone angle (negative) can lead to higher downstream but lower upstream turbine performance, compared with a non-tilted turbine. Despite the optimal precone angle of the upstream wind turbine is 0°, a -2.5° proves more advantageous owing to the large flexible deformation of the turbine wingtips. The findings can serve as a continuous incentive for improving wind farm numerical simulation.