Small-Scale Wind Turbine Testing in Wind Tunnels Under Low Reynolds Number Conditions

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
Kenneth W. Van Treuren
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Reynolds Numbers ◽  
Wind Tunnels ◽  
Small Scale ◽  
Predicting Performance ◽  
Accurate Design ◽  
Low Reynolds ◽  
Lift And Drag ◽  
Turbine Airfoils

Much of the aerodynamic design of wind turbines is accomplished using computational tools such as XFOIL. These codes are not robust enough for predicting performance under the low Reynolds numbers found with small-scale wind turbines. Wind tunnels can experimentally test wind turbine airfoils to determine lift and drag data over typical operating Reynolds numbers. They can also test complete small wind turbine systems to determine overall performance. For small-scale wind turbines, quality experimental airfoil data at the appropriate Reynolds numbers are necessary for accurate design and prediction of power production.

Design Considerations, Performance Enhancing Techniques, and Wind Tunnel Testing for Small-Scale, Low Reynolds Number Wind Turbines

2011 ◽  
Author(s):  
Jason R. Gregg ◽  
Timothy A. Burdett ◽  
Kenneth W. Van Treuren ◽  
Stephen T. McClain
Keyword(s):  
Reynolds Number ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Low Reynolds Number ◽  
Small Scale ◽  
Wind Tunnel Testing ◽  
Low Reynolds ◽  
Lift And Drag

Wind turbines have become a significant part of the world’s energy equation and are expected to become even more important in the years to come. A much-neglected area within wind turbine research is small-scale, fixed-pitch wind turbines with typical power outputs in the 1–10 kW range. This size wind system would be ideal for residential and small commercial applications. The adoption of these systems could reduce dependence on the aging U.S. power grid. It is possible to optimize a small-scale system to operate more efficiently at lower wind speeds, which will make wind generation possible in areas where current wind technology is not feasible. This investigation examines the use of the S818 airfoil, a typical blade root airfoil designed by the National Renewable Energy Laboratory (NREL), as a basis for the design of low Reynolds number (less than 200,000) systems. The literature shows that many of the airfoils proposed for wind turbine applications, including the S818, only have lift and drag data generated by numerical simulations. In previous research at Baylor, 2-D simulations published by NREL have been shown to predict an optimal design angle of attack (which is the angle at which L/D is maximized) up to 2.25° different from actual wind tunnel data. In this study, the lift and drag generated by the S818 airfoil has been measured experimentally at a Reynolds number of approximately 150,000 and compared with NREL simulation data, showing a discrepancy of 1.0°. Using the S818 airfoil, a set of wind turbine blades has been designed to collect wind turbine power data in wind tunnel testing. Design parameters investigated include the effect of design tip speed ratios (TSR) (1, 3, and 7) and the influence of the number of blades (2, 3 and 4) on power generated. At the low Reynolds numbers tested (ranging from 14,000–43,200 along the blade for a design TSR of 3 and a wind speed of 10 mph), the effect of roughness was explored as a performance enhancing technique and was seen to increase power output by delaying separation. Under these low Reynolds number conditions, separation typically occurs on smooth blades. However, the roughness acted as a passive flow control, keeping the flow attached and increasing power output. Preliminary data suggest that as much as a 50% improvement can be realized with the addition of roughness elements for a TSR of 3. Additionally, the increase in power output due to roughness is comparable with the increase in power due to adding another smooth blade.

An Examination of the Effect of Reynolds Number on Airfoil Performance

2011 ◽  
Author(s):  
Tim Burdett ◽  
Jason Gregg ◽  
Kenneth Van Treuren
Keyword(s):  
Experimental Data ◽  
Reynolds Number ◽  
Wind Turbines ◽  
Large Scale ◽  
Reynolds Numbers ◽  
Energy Sources ◽  
Small Scale ◽  
Number Range ◽  
Low Reynolds Numbers ◽  
Low Reynolds

The standard of living throughout the world has increased dramatically over the last 30 years and is projected to continue to rise. This growth leads to an increased demand on conventional energy sources, such as fossil fuels. However, these are finite resources. Thus, there is an increasing demand for alternative energy sources, such as wind energy. Much of current wind turbine research focuses on large-scale (>1 MW), technologically-complex wind turbines installed in areas of high average wind speed (>20 mph). An alternative approach is to focus on small-scale (1–10kW), technologically-simple wind turbines built to produce power in low wind regions. While these turbines may not be as efficient as the large-scale systems, they require less industrial support and a less complicated electrical grid since the power can be generated at the consumer’s location. To pursue this approach, a design methodology for small-scale wind turbines must be developed and validated. This paper addresses one element of this methodology, airfoil performance prediction. In the traditional design process, an airfoil is selected and published lift and drag curves are used to optimize the blade twist and predict performance. These published curves are typically generated using either experimental testing or a numeric code, such as PROFIL (the Eppler Airfoil Design and Analysis Code) or XFOIL. However, the published curves often represent performance over a different range of Reynolds numbers than the actual design conditions. Wind turbines are typically designed from 2-D airfoil data, so having accurate airfoil data for the design conditions is critical. This is particularly crucial for small-scale, fixed-pitched wind turbines, which typically operate at low Reynolds numbers (<500,000) where airfoil performance can change significantly with Reynolds number. From a simple 2-D approach, the ideal operating condition for an airfoil to produce torque is the angle of attack at which lift is maximized and drag is minimized, so prediction of this angle will be compared using experimental and simulated data. Theoretical simulations in XFOIL of the E387 airfoil, designed for low Reynolds numbers, suggest that this optimum angle for design is Reynolds number dependent, predicting a difference of 2.25° over a Reynolds number range of 460,000 to 60,000. Published experimental data for the E387 airfoil demonstrate a difference of 2.0° over this same Reynolds number range. Data taken in the Baylor University Subsonic Wind Tunnel for the S823 airfoil shows a similar trend. This paper examines data for the E387 and S823 airfoils at low Reynolds numbers (75,000, 150,000, and 200,000 for the S823) and compares the experimental data with XFOIL predictions and published PROFIL predictions.

scholarly journals Design and Analysis of a Wind Turbine Blade with Dimples to Enhance the Efficiency through CFD with ANSYS R16.0

2018 ◽  
Vol 207 ◽  
pp. 02004
Author(s):  
M. Rajaram Narayanan ◽  
S. Nallusamy ◽  
M. Ragesh Sathiyan
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Turbine Blades ◽  
Electrical Energy ◽  
Optimum Combination ◽  
Surface Topology ◽  
Wind Turbine Blades ◽  
Lift And Drag

In the global scenario, wind turbines and their aerodynamics are always subjected to constant research for increasing their efficiency which converts the abundant wind energy into usable electrical energy. In this research, an attempt is made to increase the efficiency through the changes in surface topology of wind turbines through computational fluid dynamics. Dimples on the other hand are very efficient in reducing air drag as is it evident from the reduction of drag and increase in lift in golf balls. The predominant factors influencing the efficiency of the wind turbines are lift and drag which are to be maximized and minimized respectively. In this research, surface of turbine blades are integrated with dimples of various sizes and arrangements and are analyzed using computational fluid dynamics to obtain an optimum combination. The analysis result shows that there is an increase in power with about 15% increase in efficiency. Hence, integration of dimples on the surface of wind turbine blades has helped in increasing the overall efficiency of the wind turbine.

scholarly journals The transient swimming of a waving sheet

2009 ◽  
Vol 466 (2113) ◽  
pp. 107-126 ◽  
Author(s):  
On Shun Pak ◽  
Eric Lauga
Keyword(s):  
Fluid Flow ◽  
Reynolds Numbers ◽  
Geometrical Model ◽  
Small Scale ◽  
Transient Effects ◽  
Initial Value ◽  
Low Reynolds Numbers ◽  
The Past ◽  
Low Reynolds Number Swimming ◽  
Low Reynolds

Small-scale locomotion plays an important role in biology. Different modelling approaches have been proposed in the past. The simplest model is an infinite inextensible two-dimensional waving sheet, originally introduced by Taylor, which serves as an idealized geometrical model for both spermatozoa locomotion and ciliary transport in Stokes flow. Here, we complement classic steady-state calculations by deriving the transient low-Reynolds number swimming speed of such a waving sheet when starting from rest (small-amplitude initial-value problem). We also determine the transient fluid flow in the ‘pumping’ setup where the sheet is not free to move but instead generates a net fluid flow around it. The time scales for these two problems, which in general govern transient effects in transport and locomotion at low Reynolds numbers, are also derived using physical arguments.

Wake Analysis of a Finite Width Gurney Flap

2015 ◽  
Author(s):  
D. Holst ◽  
A. B. Bach ◽  
C. N. Nayeri ◽  
C. O. Paschereit ◽  
G. Pechlivanoglou
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Large Scale ◽  
Reynolds Numbers ◽  
Tip Vortex ◽  
Finite Width ◽  
Low Reynolds Numbers ◽  
Gurney Flaps ◽  
Gurney Flap ◽  
Pitch System

The results of stereo Particle-Image-Velocimetry measurements are presented in this paper to gain further insight into the wake of a finite width Gurney flap. It is attached to an FX 63-137 airfoil which is known for a very good performance at low Reynolds numbers and is therefore used for small wind turbines and is most appropriate for tests in the low speed wind tunnel presented in this study. The Gurney flaps are a promising concept for load control on wind turbines but can have adverse side effects, e.g. shedding of additional vortices. The investigation focuses on frequencies and velocity distributions in the wake as well as on the structure of the induced tip vortices. Phase averaged velocity fields are derived of a Proper-Orthogonal-Decomposition based on the stereo PIV measurements. Additional hot-wire measurements were conducted to analyze the fluctuations downstream of the finite width Gurney flaps. Experiments indicate a general tip vortex structure that is independent from flap length but altered by the periodic shedding downstream of the flap. The influence of Gurney flaps on a small wind turbine is investigated by simulating a small 40 kW turbine in Q-Blade. They can serve as power control without the need of an active pitch system and the starting performance is additionally improved. The application of Gurney flaps imply tonal frequencies in the wake of the blade. Simulation results are used to estimate the resulting frequencies. However, the solution of Gurney flaps is a good candidate for large scale wind turbine implementation as well. A FAST simulation of the NREL 5MW turbine is used to generate realistic time series of the lift. The estimations of control capabilities predict a reduction in the standard deviation of the lift of up to 65%. Therefore finite width Gurney flaps are promising to extend the lifetime of future wind turbines.

Static and Dynamic Analysis of a NACA 0021 Airfoil Section at Low Reynolds Numbers: Drag and Moment Coefficients

2019 ◽  
Author(s):  
David Holst ◽  
Francesco Balduzzi ◽  
Alessandro Bianchini ◽  
Christian Navid Nayeri ◽  
Christian Oliver Paschereit ◽  
...  
Keyword(s):  
Experimental Data ◽  
Wind Tunnel ◽  
Wind Turbines ◽  
Reynolds Numbers ◽  
Correction Method ◽  
Hysteresis Cycle ◽  
Low Reynolds Numbers ◽  
Static And Dynamic Analysis ◽  
Wide Range ◽  
Low Reynolds

Abstract Wind industry needs high quality airfoil data for a range of the angle of attack (AoA) much wider than that often provided by the technical literature, which often lacks data i.e. in deep- and post-stall region. Especially in case of vertical axis wind turbines (VAWTs), the blades operate at very large AoAs, which exceed the range of typical aviation application. In a previous study, some of the authors analyzed the trend of the lift coefficient of a NACA 0021 airfoil, using the suggestions provided by detailed CFD analyses to correct experimental data at low Reynolds numbers collected in an open-jet tunnel. In the present study, the correction method is extended in order to analyze even the drag and moment coefficients over a wide range of AoAs for two different Reynolds numbers (Re = 140k and Re = 180k) of particular interest for small wind turbines. The utility of these data is again specifically high in case of VAWTs, in which both the drag and the moment coefficient largely contribute to the torque. The investigation involves tunnel data regarding both static polars and dynamic sinusoidal pitching movements at multiple reduced frequencies. Concerning the numerical simulations, two different computational domains were considered, i.e. the full wind tunnel and the open field. Once experimental data have been purged by the influence of the wind tunnel by means of the proposed correction method, they were compared to existing data for similar Reynolds both for the NACA0021 and for similar airfoils. By doing so, some differences in the static stall angle and the extent of the hysteresis cycle are discussed. Overall, the present paper provides the scientific community with detailed analysis of low-Reynolds NACA 0021 data in multiple variations, which may enable, inter alia, a more effective VAWT design in the near future.

scholarly journals Numerical Investigations of the Effects of the Rotating Shaft and Optimization of Urban Vertical Axis Wind Turbines

Energies ◽  
2018 ◽  
Vol 11 (7) ◽  
pp. 1870 ◽  
Author(s):  
Lidong Zhang ◽  
Kaiqi Zhu ◽  
Junwei Zhong ◽  
Ling Zhang ◽  
Tieliu Jiang ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Suction Side ◽  
Vertical Axis ◽  
Power Coefficient ◽  
Small Scale ◽  
Physical Parameters ◽  
Rotating Shaft ◽  
Vertical Axis Wind Turbines ◽  
Negative Effect

The central shaft is an important and indispensable part of a small scale urban vertical axis wind turbines (VAWTs). Normally, it is often operated at the same angular velocity as the wind turbine. The shedding vortices released by the rotating shaft have a negative effect on the blades passing the wake of the wind shaft. The objective of this study is to explore the influence of the wake of rotating shaft on the performance of the VAWT under different operational and physical parameters. The results show that when the ratio of the shaft diameter to the wind turbine diameter (α) is 9%, the power loss of the wind turbine in one revolution increases from 0% to 25% relative to that of no-shaft wind turbine (this is a numerical experiment for which the shaft of the VAWT is removed in order to study the interactions between the shaft and blade). When the downstream blades pass through the wake of the shaft, the pressure gradient of the suction side and pressure side is changed, and an adverse effect is also exerted on the lift generation in the blades. In addition, α = 5% is a critical value for the rotating shaft wind turbine (the lift-drag ratio trend of the shaft changes differently). In order to figure out the impacts of four factors; namely, tip speed ratios (TSRs), α, turbulence intensity (TI), and the relative surface roughness value (ks/ds) on the performance of a VAWT system, the Taguchi method is employed in this study. The influence strength order of these factors is featured by TSRs > ks/ds > α > TI. Furthermore, within the range we have analyzed in this study, the optimal power coefficient (Cp) occurred under the condition of TSR = 4, α = 5%, ks/ds = 1 × 10−2, and TI = 8%.

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