CFD Study of a Darreous Vertical Axis Wind Turbine Md Nahid Pervez a and Wael Mokhtar b a Graduate Assistant b PhD. Assistant Professor Grand Valley State University, Grand Rapids, MI 49504 E-mail:, mokhtarw@gvsu.edu Introduction GO GREEN! is a widely used buzzword of these days for most of the companies and even for the policy makers. Some significant steps for saving the environment are - recycling the pop cans, using bio-degradable packaging materials, reducing the wastage of papers, using more efficient electric appliances, and using more efficient cars. But how far are we in the journey to going green? In the year 2010 only eight percent of the total 98.1 quads of energy consumption of US came from renewable energy sources 1 which roughly is eight quads, in which only 12% of the energy is from the wind energy 1. So the statistics tell us that we still have a long way to go. US government has a plan to obtain 20% of the total electric energy supply from renewable energy sources by the year 2030 2. Wind energy offers a promising renewable energy source and wind turbines are the only way to extract energy from the wind. HAWT (Horizontal Axis Wind Turbines) are widely used from the early days to harvest the wind energy. However VAWT (Vertical Axis Wind Turbine) are relatively new technology and proved to be very effective in lower wind speed locations such as cities. CFD (Computational Fluid Dynamics) is a very powerful tool for examining the flow characteristics of a complex system like the HAWT. In this paper, flow characteristics around a VAWT is presented using CFD tool. Literature Review A technical study was presented by D. Ayhan et. al. 3 about the wind speed variations and flow characteristics in city area. The boundary layer in a city, effect of building geometry on the boundary layer and the micro wind flow around the buildings were presented with the help of CFD tools. Different types of turbines for harnessing the energy were also suggested in that paper. An experimental study was done by R. Howell et. al. 4. The airfoil analyzed in that study was NACA 0022. The chord length of the turbine was 100 mm and the length was limited to 400 mm. they did experiment on both 2 bladed (solidity of 1) and 3 bladed turbines (solidity of 0.67). The low speed wind tunnel where the tests were performed had a square test section of 1.2m X 1.2m dimension. The reason for that experiment was to get a set of experimental results to compare with a CFD model. From the study it was found that the predicted performance from
the 2D study was much higher than the 3D experimental results. Dynamic behavior of vortices over the tip of the turbine blade is responsible for that, according to the authors. A CFD study of an unconventionally designed VAWT was presented by S. McTavish et. al. 5. The authors made a CFD model of a wind turbine of novel design for mainly micro scale power generation. Several modifications of a VAWT are experimented and studied to improve the power coefficient of the VAWT. One particular modification is incorporating a stator guide vane. A CFD study on that is presented by K. Pope et. al. 6. A zephyr made VAWT was studied in that paper. One particular problem of a VAWT is, it is not self-starting. To eliminate this problem asymmetric airfoils are used normally. An experimental study was performed on a VAWT with asymmetric airfoil by M. Takao et. al. 7. The airfoil used in that study was NACA4518 with stator guide vane. Present Work For the simulation of a VAWT, a step by step work flow was maintained. In the beginning, a 2D analysis was performed for the NACA4518 airfoil and its performance was observed for low speed wind. A profile of a NACA4518 is shown in figure 1. 20 10 0-20 -10 0 20 40 60 80 100 120 140 NACA 4518 Figure 1: Profile of a NACA4518 airfoil As the airfoil was a blade of a VAWT, it would be subjected to positive and negative angle of attack. So the angle of attack was varied from -12 to +12. And the results are presented. Then a 3D model of an airfoil was simulated. Like the 2D analysis, the results of negative and positive angle of attack are presented. And finally a simplified 3D model of a VAWT with 3 blades was simulated. The airflow structure and other major flow characteristics around the turbine were presented. All of the models of the wind turbine used in the study were done by the CAD software SolidWorks TM. The length of the wind turbine was 1.514 m (5 feet). The chord length was 0.127 m (5 inch). CAD models are shown in figures 2, 3 and 4.
Figure 2 2D model Figure 3 3D model Figure 4 Simplified turbine model The applicability of VAWT in the city area is promising. So throughout the analysis the wind speed was maintained at 6.71 m/s (15 mph). It is the average speed of the city of Johnston Island, PC 8. The reason for this city is, it has a very decent wind speed throughout the year 8. Same wind speed was maintained for the 2D, 3D and simplified turbine model. The angle of attack was varied to observe the characteristics for 2D and 3D. Table 1 displays a summary of the different simulations. Table 1 Simulation Type Angle of Attack Speed (m/s) 2D Model -12, -8, -4, 0, 4, 8, 12 6.71 3D Model -8, -4, 0, 4, 8 6.71 Rotation of the simplified turbine model was simulated by applying a tangential velocity at the walls of the rotor. The rotational velocity was 100 rpm. The orientation of the simplified model of the turbine was rotated from 0 to 120. The full performance in the whole 360 region is found by just repeating the results from 0 to 120. Table 2 shows the different orientations of the rotor that were simulated. Table 2 Simulation Type Orientation Angle Speed (m/s) Simplified 3D model of the turbine rotor. 0, 15,30,45,60,75,90 6.71,105,120 Computational Method The simulations were performed using STAR CCM+ TM commercial software. It was developed by CD-Adapco, Inc. and uses computational finite volume method for solving. For this study segregated flow solver was used. SST k- turbulence model was used for turbulence model. For the 2D study the numerical domain had a thickness of one chord length of the airfoil. The size of the numerical domain was large enough so that the domain boundary do not affect the simulation results. Figure 5 shows the meshed numerical domain with the airfoil inside it. Note that the mesh on that figure 5 is the surface mesh. For the surface mesh, surface remesher model was used. Trimmer volume mesh model was used to generate the volume mesh. The cells were
clustered to capture the curvature of the airfoil. Figure 7 shows the growth rate of the mesh as it moves outward in the domain. Figures 6 and 7 show the surface and volume mesh of the 2D airfoil respectively. Figure 5 2D surface mesh of numerical domain Figure 6 2D surface mesh of airfoil Figure 7 2D volume mesh of numerical domain Figure 8 2D volume mesh of airfoil Near the airfoil, to capture the boundary layer, prism layers were used. The thickness of the boundary layer was determined by repetitive trials so that it can capture the physics of boundary layer. Volumetric control was also used to cluster the cells around the airfoil to capture the turbulence and flow separation. Figures 9 and 10 show the boundary layer and the volumetric control region of the 2D study respectively.
Figure 9 Prism layers to capture boundary layer Figure 10 Volumetric control to cluster cells around the airfoil Similar approach was followed to simulate the 3D airfoil. For the 3D case only half of the airfoil simulated with a symmetric boundary to reduce the computational time. Figures 11 and 13 show the numerical domain with surface mesh and volume mesh for 3D case respectively. Figures 12 and 14 show the airfoil with surface mesh and volume mesh respectively.
Figure 11 Surface mesh of domain of 3D model Figure 12 Surface mesh of airfoil of 3D model Figure 13 Volume mesh of domain of 3D model Figure 14 Volume mesh of airfoil of 3D model For the simplified turbine model the numerical domain had a shape of cylinder. Volumetric control was used to cluster the cells around the turbine to capture the physics more accurately. Boundary layer was used to capture the boundary layer. Figures 15 and 16 show the surface meshes of the numerical domain and the rotor and figures 17 and 18 show the volume mesh of those. Figure 15 Surface mesh of numerical domain Figure 16 Surface mesh of simplified turbine
Figure 17 Volume mesh of numerical domain Figure 18 Volume mesh of simplified turbine The cell size was increased as it moves outward from the turbine. Figure 19 show the volumetric control of the cell and gradual increase of the cell size. Figure 19 Volumetric control to cluster cells around the turbine
The major parameters of the 2D and 3D cases are tabulated in table 3. Table 3 Parameters 2D Airfoil 3D airfoil Simplified Turbine Geometry: Chord length : 0.127 m (5 inch) Speed: 6.71 m/s (15 mph) Chord length : 0.127 m (5 inch) Length : 0.762 m (2.5 feet) Chord length : 0.127 m (5 inch) Length : 1.524 m (5 feet) Reynolds number: Speed: 6.71 m/s (15 L/D ratio: 12 58300 mph) Width of the turbine: Reynolds number: 3 feet 58300 Speed: 6.71 m/s (15 mph) Model: Trimmer volume Trimmer volume Trimmer volume mesh mesh mesh Number of cells: Number of cells: Number of cells: 216840 883204 623416 Segregated flow SST k-ω turbulence model Segregated flow SST k-ω turbulence model Segregated flow SST k-ω turbulence model Solver: AMG linear solver AMG linear solver AMG linear solver CFD Results and Discussions The 2D analysis was performed to characterize the performance of the airfoil. One of the major challenges for CFD is to capture the boundary layer and separation region properly. Figure 20 shows the boundary layer and the prism layers used to capture it. Figure 20 Prism layers capturing the boundary layer
From the pressure contour (figure 21) and the velocity vector around the airfoil (figure 22) the stagnation point is visible. A minute separation region is also found from the velocity vector (figure 22). Figure 23 show the stream line around the airfoil. Note that all of the results are of the 0 angle of attack simulation. Figure 21 Pressure contours around the airfoil for 2D case Figure 22 Velocity distribution around the airfoil for 2D case Figure 23 Streamline around the airfoil for 2D case The coefficient of lift is the most important result for this simulation. The airfoil will be subjected to a variable angle of attack both in positive and negative direction. So both positive and negative angle of attack cases were simulated. Coefficients of lift for different angles of attack are shown in figure 24 for 2D simulation. Lift coefficient 1 0.8 0.6 0.4 0.2 0-20 -10-0.2 0 10 20-0.4-0.6 Angle of attack Figure 24 Lift of coefficient for 2D simulation Lift Coefficient 1 0.8 0.6 0.4 0.2 0-10 -0.2 0 10-0.4-0.6-0.8 Angle of attack Figure 25 Lift of coefficient for 3D simulation
The 3D simulations were done in a similar fashion. The coefficients of lift for different angles of attack can be found in figure 25. Notable fact is that, the performance parameter which is the coefficients of lift of the airfoil decreases in 3D simulation cases. The coefficient of lift has the highest value of 0.75 in 3D case where in 2D case the highest value was 0.84. One of the main objectives of this study was to visualize the flow structure around the VAWT wind turbine. The complexity of the flow structure makes it hard to visualize. Figure 26 shows the stream lines around the turbine. The turbine blades were used to seed the streamlines. Figure 26 Streamline around the simplified turbine The velocity magnitude around the turbine in figure 27 shows a large separation of flow region due to the orientation of the airfoil. The lift generated by the wing would provide the moment or torque to rotate. So at different orientations the torque would be different. In current orientation, among the three blades one blade is facing the wind in a perpendicular position which is creating a huge separation region.
Figure 27 Velocity profile around the turbine The pressure contour around the rotor in figure 28 is supporting the fact of separation of flow due to orientation of the blades. Figure 28 Pressure contours around the turbine The rotational velocity of the simplified turbine was simulated by adding a tangential velocity. A closer look on the velocity vector around the blades from figure 29 shows the tangential velocity.
Figure 29 Velocity distribution at the vicinity of the turbine wall The moment is the main indicator for the turbine power generation. But the moment varies due to the different orientation of the blades. The wind direction was varied from 0 to 120 and the moment around the rotor calculated from the simulation. As it is a 3 bladed rotor, the moments at other angles were found by repeating the results. Figure 30 show moments generated by the rotor. 0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 0 50 100 150 200 250 300 350 Moment at angle Average moment Figure 30 Moment generated by turbine The average torque was found 0.1144 N-m at 100 rpm. The turbine produces 1.198 watt of power. The results show that the turbine has a very low efficiency. Further modification of the turbine structure and proper modeling of the turbine in CFD will provide more accurate results.
Conclusion CFD is very effective for visualizing the complex flow structure around the vertical axis wind turbine. This study had primary objective to visualize the flow structure, analyze the performances of the airfoil NACA 4518 and act as preliminary study for a complex unsteady analysis of a VAWT. 2D, 3D and simplified model of a VAWT is simulated and results are presented in this study. The flow structure is presented for the simplified turbine in the form of streamlines. Performance parameter which is the coefficient of lift is presented for different angle of attacks. Performance differences in 2D and 3D studies are also observed. For simplicity, the rotational motion of the turbine was simulated by adding tangential velocity on the walls of the rotor. This is a simplified approach to a complex fluid-solid interaction problem. From th performance of the VAWT is relatively lower than that of a HAWT. However significant structural modifications and proper mathematical modeling will provide accurate results. References 1. U. S. DOE, Energy Information Administration (EIA) (2011) Monthly Energy Review September 2011 2. U. S.DOE, Energy Efficiency and Renewable Energy 20% Wind Energy by 2030 July 2008 3. Ayhan, D., Saglam, S., A technical review of building-mounted power systems and a sample simulation model, Renewable and Sustainable Energy Reviews 16 (2012) 1040-1049 4. Howell, R., Qin, N., Edwards, J., Durrani, N., Wind tunnel and numerical study of a small vertical axis wind turbine, Renewable Energy 35 (2010) 412-422 5. Mctavish, S., Feszty, D., Sankar, T., Steady and rotating computational fluid dynamics simulations of a novel vertical axis wind turbine for small-scale power generation, Renewable Energy 41 (2012) 171-179 6. Pope, K., Rodrigues, V., Doyle, R., Tsopelas, A., Gravelsins, R., Naterer, G. F., Tsang, E., Effect of stator vanes on power coefficients of a zephyr vertical axis wind turbine, Renewable Energy 35 (2010) 1043-1051 7. Takao, M., Kuma, H., Maeda, T., Kamada, Y., Oki, M., Minoda, A., A Straight-bladed Vertical Axis Wind Turbine with a Direct Guide Vane Row Effect of Guide Vane Geometry on the Performance, Journal of thermal Science Vol. 18, No. 1 (2009) 54-57 8. Comparative Climatic Data, Wind Average Wind Speed (MPH), Retrieved from the web on December 2011, site: http://lwf.ncdc.noaa.gov/oa/climate/online/ccd/avgwind.html, National Climatic Data Center, U. S. Department of Commerce.