scholarly journals A Comparison of Predicted Wind Turbine Blade Loads to Test Measurements

1988 ◽  
Vol 110 (3) ◽  
pp. 180-186 ◽  
Author(s):  
A. D. Wright ◽  
R. W. Thresher

The accurate prediction of wind turbine blade loads and response is important in predicting the fatigue life of wind machines. At the SERI Wind Energy Research Center, a rotor code called FLAP (Force and Loads Analysis Program) is currently being validated by comparing predicted results to machine measurements. The FLAP code has been modified to allow the teetering degree of freedom. This paper describes these modifications and comparisons of predicted blade bending moments to test measurements. Wind tunnel data for a 1/20th scale model will be used to compare FLAP predictions for the cyclic flap-bending moments at the 33 percent spanwise station for three different wind speeds. The comparisons will be made for both rigid and teetering hubs. Currently, the FLAP code accounts for deterministic excitations such as wind shear, tower shadow, gravity, and prescribed yawing motions. Conclusions will be made regarding the code’s accuracy in predicting the cyclic bending moments.

Wind Energy ◽  
2000 ◽  
Vol 3 (1) ◽  
pp. 35-65 ◽  
Author(s):  
K. Papadopoulos ◽  
E. Morfiadakis ◽  
T. P. Philippidis ◽  
D. J. Lekou

Author(s):  
Alka Gupta ◽  
Abdulrahman Alsultan ◽  
R. S. Amano ◽  
Sourabh Kumar ◽  
Andrew D. Welsh

Energy is the heart of today’s civilization and the demand seems to be increasing with our growing population. Alternative energy solutions are the future of energy, whereas the fossil-based fuels are finite and deemed to become extinct. The design of the wind turbine blade is the main governing factor that affects power generation from the wind turbine. Different airfoils, angle of twist and blade dimensions are the parameters that control the efficiency of the wind turbine. This study is aimed at investigating the aerodynamic performance of the wind turbine blade. In the present paper, we discuss innovative blade designs using the NACA 4412 airfoil, comparing them with a straight swept blade. The wake region was measured in the lab with a straight blade. All the results with different designs of blades were compared for their performance. A complete three-dimensional computational analysis was carried out to compare the power generation in each case for different wind speeds. It was found from the numerical analysis that the slotted blade yielded the most power generation among the other blade designs.


2018 ◽  
Vol 7 (3.27) ◽  
pp. 456
Author(s):  
Albi . ◽  
M Dev Anand ◽  
G M. Joselin Herbert

The aerofoils of wind turbine blades have crucial influence on aerodynamic efficiency of wind turbine. There are numerous amounts of research being performed on aerofoils of wind turbines. Initially, I have done a brief literature survey on wind turbine aerofoil. This project involves the selection of a suitable aerofoil section for the proposed wind turbine blade. A comprehensive study of the aerofoil behaviour is implemented using 2D modelling. NACA 4412 aerofoil profile is considered for analysis of wind turbine blade. Geometry of this aerofoil is created using GAMBIT and CFD analysis is carried out using ANSYS FLUENT. Lift and Drag forces along with the angle of attack are the important parameters in a wind turbine system. These parameters decide the efficiency of the wind turbine. The lift force and drag force acting on aerofoil were determined with various angles of attacks ranging from 0° to 12° and wind speeds. The coefficient of lift and drag values are calculated for 1×105 Reynolds number. The pressure distributions as well as coefficient of lift to coefficient of drag ratio of this aerofoil were visualized. The CFD simulation results show close agreement with those of the experiments, thus suggesting a reliable alternative to experimental method in determining drag and lift.


2018 ◽  
Vol 1037 ◽  
pp. 062022 ◽  
Author(s):  
Matthew Harrison ◽  
Menno Kloosterman ◽  
Ricard Buils Urbano

2016 ◽  
Vol 753 ◽  
pp. 022028 ◽  
Author(s):  
I. Bayati ◽  
M. Belloli ◽  
L. Bernini ◽  
R. Mikkelsen ◽  
A. Zasso

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