The influence of atmospheric stability on the ?Leipzig? boundary-layer structure

1989 ◽  
Vol 46 (3) ◽  
pp. 207-227 ◽  
Author(s):  
G. Riopelle ◽  
G. D. Stubley
2019 ◽  
pp. 0309524X1988092
Author(s):  
Mohamed Marouan Ichenial ◽  
Abdellah El-Hajjaji ◽  
Abdellatif Khamlichi

The assessment of climatological site conditions, airflow characteristics, and the turbulence affecting wind turbines is an important phase in developing wake engineering models. A method of modeling atmospheric boundary layer structure under atmospheric stability effects is crucial for accurate evaluation of the spatial scale of modern wind turbines, but by themselves, they are incapable to account for the varying large-scale weather conditions. As a result, combining lower atmospheric models with mesoscale models is required. In order to realize a reasonable approximation of initial atmospheric inflow condition used for wake identification behind an NREL 5-MW wind turbine, different vertical wind profile models on equilibrium conditions are tested and evaluated in this article. Wind farm simulator solvers require massive computing resources and forcing mechanisms tendencies inputs from weather forecast models. A three-dimensional Flow Redirection and Induction in Steady-state engineering model was developed for simulating and optimizing the wake losses of different rows of wind turbines under different stability stratifications. The obtained results were compared to high-fidelity simulation data generated by the famous Simulator for Wind Farm Applications. This work showed that a significant improvement related to atmospheric boundary layer structure can be made to develop accurate engineering wake models in order to reduce wake losses.


2021 ◽  
Vol 920 ◽  
Author(s):  
Nathaniel R. Bristow ◽  
Gianluca Blois ◽  
James L. Best ◽  
Kenneth T. Christensen

Abstract


2020 ◽  
Vol 5 (11) ◽  
Author(s):  
Robert S. Long ◽  
Jon E. Mound ◽  
Christopher J. Davies ◽  
Steven M. Tobias

Sign in / Sign up

Export Citation Format

Share Document