Investigation of the incoming wind vector for improved wind turbine yaw-adjustment under different atmospheric and wind farm conditions

RENEWABLE ENERGY

卷:101

Article

Cortina, G.¹  Sharma, V.²  Calaf, M.¹ 

[1] Univ Utah, Dept Mech Engn, Salt Lake City, UT 84112 USA

[2] Ecole Polytech Fed Lausanne, Sch Architecture Civil & Environm Engn, Lausanne, Switzerland

关键词: Large eddy simulation;    LIDAR;    Wind energy;    Wind farm;    Wind turbines;    Yaw-misalignment;   

DOI  :  10.1016/j.renene.2016.08.011

来源: Elsevier

【 摘 要 】

Regardless of the evolution of wind energy harvesting, the way in which turbines obtain in-situ meteorological information remains the same - i.e. using traditional wind vanes and cup anemometers installed at the turbine's nacelle, right behind the blades. As a result, misalignment with the mean wind vector is common and energy losses up to 4.6% can be experienced as well as increases in loading and structural fatigue. A solution for the near-blade monitoring is to install wind LIDAR devices on the turbines' nacelle. This technique is currently under development as an alternative to traditional in-situ wind anemometry because it can measure the wind vector at substantial distances upwind. But at what upwind distance should they interrogate the atmosphere? and, what is the optimal average time in which to learn about the incoming flow conditions? This work simulates wind fields approaching isolated wind turbines and wind turbine arrays within large wind farms using Large Eddy Simulations. The goal is to investigate the existence of an optimal upstream scanning distance and average time for wind turbines to measure the incoming wind conditions under different ambient atmospheric conditions. Results reveal no significant differences when measuring the incoming wind vector at different upstream distances, regardless of the atmospheric stratification. Within this framework a 30 min readjustment period is observed to perform the best. (C) 2016 Elsevier Ltd. All rights reserved.

【 授权许可】

Free