scholarly journals Wind farm power optimization via yaw angle control: A wind tunnel study

2019 ◽  
Vol 11 (2) ◽  
pp. 023301 ◽  
Author(s):  
Majid Bastankhah ◽  
Fernando Porté-Agel
Energies ◽  
2011 ◽  
Vol 4 (11) ◽  
pp. 1916-1936 ◽  
Author(s):  
Leonardo P. Chamorro ◽  
Fernando Porté-Agel

1978 ◽  
Vol 100 (4) ◽  
pp. 434-438 ◽  
Author(s):  
F. T. Buckley ◽  
C. H. Marks

The effect of gap width on the aerodynamic drag of a cab-over-engine tractor-trailer combination has been investigated for full-scale gap widths ranging from 0.61 m (24 in) to 1.83 m (72 in.) over a yaw angle range of 0 to 20 deg. The average drag on the vehicle was found to increase by 16 percent as the gap width increased from 0.61 m to 1.83 m. Drag reductions were found when a vertical seal was placed along the vehicle center line between the tractor and the trailer. Generally, the drag reduction increased as the percentage of gap width that was sealed increased, and as the yaw angle increased. The average drag coefficient reduction provided by a full gap seal increased from 0.02 to 0.05 as the gap width increased from 0.61 m to 1.4 m and then decreased slightly for gap widths up to 1.83 m. The effect of vehicle configuration on gap seal effectiveness was evaluated for a gap width of 1.3 m (51 in.) using models of six different tractors and two different trailers. The average drag coefficient reductions that were found ranged from 0.04 to 0.08 with 83 percent of the data being either 0.04 or 0.05. It is shown that the use of gap seals on the nearly half-million vehicles which comprise the nation’s long-haul trucking fleet can result in the conservation of about 1.4 × 109 liters (0.37 × 109 gal) of motor fuel each year.


2016 ◽  
Vol 753 ◽  
pp. 072002 ◽  
Author(s):  
Juliaan Bossuyt ◽  
Michael F. Howland ◽  
Charles Meneveau ◽  
Johan Meyers

2017 ◽  
Vol 41 (5) ◽  
pp. 313-329 ◽  
Author(s):  
Jared J Thomas ◽  
Pieter MO Gebraad ◽  
Andrew Ning

The FLORIS (FLOw Redirection and Induction in Steady-state) model, a parametric wind turbine wake model that predicts steady-state wake characteristics based on wind turbine position and yaw angle, was developed for optimization of control settings and turbine locations. This article provides details on changes made to the FLORIS model to make the model more suitable for gradient-based optimization. Changes to the FLORIS model were made to remove discontinuities and add curvature to regions of non-physical zero gradient. Exact gradients for the FLORIS model were obtained using algorithmic differentiation. A set of three case studies demonstrate that using exact gradients with gradient-based optimization reduces the number of function calls by several orders of magnitude. The case studies also show that adding curvature improves convergence behavior, allowing gradient-based optimization algorithms used with the FLORIS model to more reliably find better solutions to wind farm optimization problems.


Sign in / Sign up

Export Citation Format

Share Document