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2D Numerical analysis of a VAWT wind farm for different configurations

Naveed Durrani1 and Ning Qin.2

Department of Mechanical Engineering, University of Sheffield, UK

and

Haris Hameed3 and Shahab Khushnood4

Department of Mechanical and Aerospace Engineering, University of Engineering and Technology, Taxila, Pakistan

With the global focus on exploring more efficient and cost effective wind energy based

power generation techniques, vertical axis wind turbines (VAWT) have emerged as a good option at small house hold scale. For large built-up area units having combined roof such as residential blocks etc., possibility of having a clustering of small VAWT as a wind farm is quite attractive; albeit very little is available in literature from CFD analysis perspective. This paper presents a novel 2D CFD analysis of a 2.75m diameter vertical axis wind turbine (VAWT) in a farm configuration. An urban area roof top scenario with a favorable and an adverse VAWT array configuration is analyzed. Further, the effect of variation of inter-turbine distance is also studied for these configurations. Each turbine consists of three vertically aligned NACA0022 turbine blades separated apart by an angle of 120º. Each turbine has a chord length of 0.23m. The initial results presented in this paper correspond to the freestream velocity of 12 m/sec with a tip speed ratio (TSR) variation from 1 to 4.

Interesting results are obtained from the present research for both favorable and adverse configurations. A von Karman type vortex shedding is observed in the wake of all the VAWT configurations considered. For the adverse configuration (I-type configuration in which the VAWT’s are in tandem), the performance of downwind VAWT reduces drastically. With the increase in their mutual separation distance along the flow direction, the performance drop recovers. However, still the performance is lower than a single VAWT. Whereas, for the favorable configuration (T-type configuration in which the VAWT’s are staggered), the performance of the downwind VAWT increases and is higher than a single VAWT. The performance improvement decreases with the increase in their mutual separation distance.

Nomenclature c = chord (m) CD = coefficient of dragCL = coefficient of lift Cm = coefficient of moment Cp = performance coefficient Cy = force coefficient in the y direction D = drag force (N), diameter of the wind turbine dt = time step (sec) Fx = X component of the resultant pressure force acting on the airfoil (N) Fy = Y component of the resultant pressure force acting on the airfoil (N)

1 Post Graduate Student, Department of Mechanical Engineering, AIAA member, email: ndurrani@gmail.com 2 Professor of Aerodynamics, Department of Mechanical Engineering, AIAA Associate Fellow 3 Post Graduate Student, Department of Mechanical and Aerospace Engineering 4 Professor, Department of Mechanical and Aerospace Engineering

49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition4 - 7 January 2011, Orlando, Florida

AIAA 2011-461

Copyright © 2011 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

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L = lift force r = radius of the wind turbine t = time in seconds T = time period (time taken for one complete rotation in sec) TSR = tip speed ratio (𝑟Ω

𝑉)

V∞ = freestream velocity vawt = vertical axis wind turbine α = angle of attack θ = azimuth angle Ω = rotational speed (rad/sec)

I. Introduction IND energy is being focused presently for power generation as a source of green energy; a healthy alternate to the traditional fossil fuel based methodology. Although, this concept is quite old, the serious consideration

of exploring this as a renewable energy resource was not given until recently when global warming and soaring prices of depleting natural fossil fuel posed a realistic threat to the continuation of existing methods. Wind turbines are generally bifurcated on the bases of rotation axis of their drive shaft. If it is aligned with the horizontal axis parallel to the ground, it is termed as horizontal axis wind turbine (HAWT) and the one aligned with the vertical axis that is perpendicular to the base ground is called as the vertical axis wind turbine (VAWT). The following pictures show both type of the wind turbines. The HAWT shown down is DeWind D8.2 HE 2MW wind turbine at the Veladero mine of Barrick Gold, San Juan Province, Argentina and the VAWT is 5 Kilowatt Vertical Axis Wind Turbine from Green EcoSys Company. The pictures are taken from Wikipedia (www.wikipedia.org)

Figure 1: Existing VAWT (left) and HAWT (right)

W

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Wind farm concept refers to a clustered formation of wind turbines installed at a confined space. The concept of vertical axis wind turbine (VAWT) farm for urban environment is to place multiple wind turbines in that area (for instance, on a roof top of a building) and arrange them in such a manner that a best possible output is obtained. However, the wakes / vortices generated by one turbine do interfere with the other turbines in the farm and affect their performance. It is a difficult task to isolate all the prevailing scenarios and study them accordingly. In fact, due to the changing wind speed and direction, numerous configurations are possible within a simple VAWT farm. In order to be more objective in our study, a favorable and an adverse performance scenario, as will be explained later, has been selected. This work is continuation of our previous studies [5, 6, 7] in a quest for exploring different aspects of vertical axis wind turbine which have not been delineated in the literature or have limited information.

Figure 2: VAWT Wind Farm model

The first configuration as shown in (Fig.2) is the worst scenario and the two VAWTs become collinear with the oncoming free stream air. The distance between them is two times the VAWT diameter. The distance is taken from edge to edge. The rotational speed of both VAWT’s is taken as same. The schematics of other configurations are shown in figures 3 to 5. The very high aspect ratio of the turbine blade (around 20) justifies the two dimensional simulation of the VAWT.

Figure 3: Two VAWTs placed in line with a distance of 2 times the diameter (I-type)

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Figure 4: Two VAWTs placed in line with a distance of 4 times the diameter (I-type)

Figure 5: Three VAWTs, horizontal distance of 2 times the diameter (T-type)

Figure 6: Three VAWTs, horizontal distance of 4 times the diameter (T-type)

The operating principle of a wind turbine is quite simple. It extracts the energy form the oncoming free stream wind and wakes are generated behind the turbine reducing the wind speed and increasing the turbulence. Now, if another turbine is placed in the wake of the first one, it will have an oncoming flow with slower speed and higher turbulence as compared with the free stream wind. This consequently will have less energy to be extracted by the downstream turbine. And if there are more wind turbines, as in the case of wind farm, the effect of number of wakes will simultaneously act on the turbine and its performance will be badly affected. .

Figure 7: Schematic of wake interaction in a VAWT Wind Farm (I-type)

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Until recently, the main thrust of commercial power generation through the wind turbines has been on the horizontal axis wind turbines. Not surprisingly, the data in the context of a vertical axis wind turbines is severely limited. However, some studies for horizontal axis wind turbines have been carried out and show the interference effect of a wind turbine on another in a fam. Neustadter and Spera [1] found a decrease of 10% in power output for three turbines separated by 7 rotor diameters; Elliott mentions in his review [2] a ‘considerable reduction in efficiency’ and ‘[the wind farm] produced substantially less energy’. For full wake conditions power losses of downstream turbines can be 30-40%, but when averaged over different wind directions, losses of 5-8% have been reported [3,4] . In order to reduce power losses and to improve the performance of the turbine it is necessary to obtain a good understanding of the behavior of wind turbine wakes in wind farms. Accurate modeling of both the flow over the turbine blades and the flow in the near and far wake requires massive computer resources, due to the unsteady, turbulent character of the flow.

II. Case Setup A commercial software Fluent is used for present simulation. The mesh is generated using the preprocessor of

Fluent, called Gambit. The sliding mesh concept is used. Mesh details are as follows:

Mesh info – VAWT Wind Farm I-type with two time diameter distance apart Type Cells Faces Nodes

Hybrid 107034 175536 64794 Table 1: VAWT Wind Farm model (I-type with 2D distance apart)

Mesh info – VAWT Wind Farm I-type with four time diameter distance apart

Type Cells Faces Nodes Hybrid 124256 201365 73429

Table 2: VAWT Wind Farm model (I-type with 4D distance apart)

Mesh info – VAWT Wind Farm T-type with two time diameter distance apart Type Cells Faces Nodes

Hybrid 159624 261851 96686 Table 3: VAWT Wind Farm model (T-type with 2D distance apart)

Mesh info – VAWT Wind Farm T-type with four time diameter distance apart

Type Cells Faces Nodes Hybrid 191682 309927 112739

Table 4: VAWT Wind Farm model (T-type with 4D distance apart)

1. Domain size The base line grid has inflow domain placed at 16 times the radius of the wind turbine in the upstream dimension and 18 times the radius in the downstream dimension. The top and bottom boundaries are placed 12 times the radius of the VAWT. 2. Boundary conditions All the outermost boundaries are considered as the ‘pressure farfield’ boundary conditions in Fluent. The zone housing the turbine blades is considered as the sliding zone with interface boundary condition. The surface of the turbine has no-slip boundary condition. A boundary layer mesh is generated near the turbine (airfoil) to reduce the numerical dissipation near the turbine surfaces for better computation of flow characteristics. The density based solver is chosen with second order spatial accuracy. The RNG turbulence model is employed. The variation in Y-plus over the leading turbine blade surface is observed to reach up to 35. A standard wall function is chosen for the turbulence model. The results presented are at least after 7 complete cycles when flow has established itself and are averaged over three consecutive time periods (T). The time step is chosen based on time step sensitivity (not presented in this paper) and is taken as T/400. Further details about boundary conditions and formulation of solver and turbulence model etc. can be found in Fluent © User's Manual [8].

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III. Results The results presented are at a freestream wind velocity of 12 m/sec. A TSR range from 1 to 4

is further studied for this velocity. A. I-type configuration VAWT with 2D distance apart

Figure 8 (a-d) : Contours at two different instants of Velocity (a-b) and Vorticity (c-d) for I-type VAWT with 2D apart

B. I-type configuration VAWT with 4D distance apart

Figure 9 (a-c): a. Zoom view of Grid b. Velocity contours c. Vorticity contours for I-type VAWT with 4D apart (upper

limit of vorticity magnitude is 40.

a) b)

c) d)

a) b)

c)

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C. T-type configuration VAWT with 2D distance apart

Figure 10 (a-d) : a. Stream lines b. Vorticity magnitude contours c. Velocity contours d. Zoomed view of velocity vector for T-type VAWT with 2D apart

D. T-type configuration VAWT with 4D distance apart

Figure 11(a-c) : a. Zoom view of mesh b. Velocity magnitude contours c. Vorticity magnitude contours for T-type VAWT

with 4D apart

The results from figure 8-11 show interesting flow features for all the simulated cases. A von Karman type vortex shedding is observed in all the cases. The wake interactions with the

a) b)

c)

c) d)

a) b)

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downstream VAWT are quite strong and influence the performance of the downstream VAWT remarkably.

E. Comparison of Coefficient of performance In order to obtain a quantitative comparison, the performance coefficient of all the cases is carried out and the results are plotted in figures 12-17.

Figure 12: Cp Vs TSR for I-type configuration with 2D distance apart

Figure 13: Cp Vs TSR for I-type configuration with 4D distance apart

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Figure 14: Cp Vs RPM for I-type configuration with single stand alone VAWT

Figure 15: Cp Vs TSR for T-type configuration with 2D distance apart

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Figure 16: Cp Vs TSR for T-type configuration with 4D distance apart

Figure 17: Cp Vs RPM for T-type configuration with single stand alone VAWT

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IV. Conclusions It observed that the tandem or I-type configuration is the worst case scenario in which the following VAWT is located right behind the wake of its upwind turbine. The efficiency of this VAWT is considerably reduced as compared with a single VAWT and is strongly dependant on the separation distance between the two VAWT. Higher is the separation distance; lower is the drop in performance and vice versa. For T-type configuration (in which the VAWT’s are staggered), the performance of the downwind VAWT increases and is higher than a single VAWT. It is because of the suction effects due to two upstream rotating VAWTs. The downstream VAWT gets an increased wind velocity than the freestream oncoming air. The performance improvement decreases with the increase in their mutual separation distance. It may be recommended to go for a single bigger VAWT within the allowable structural and constructional constraints, instead of multiple smaller VAWTs if their mutual spacing allows the wake generated to interact with other VAWTs with reduced velocities (I-type configuration). However, for the places where space limitation is not a problem, a staggered wind farm will be beneficial.

Acknowledgments The support from higher education commission (HEC), Pakistan is acknowledged. The first author was awarded

overseas research scholarship (ORS) from the University of Sheffield for his PhD studies and is thankfully acknowledged.

References 1H.E. Neustadter and D.A. Spera, “Method for evaluating wind turbine wake effects on wind farm performance”. Journal of Solar Energy Engineering, 107:240–243, 1985. 2D.L. Elliott, “Status of wake and array loss research”, In Windpower Conference Palm Springs, California, 1991. 3R.J. Barthelmie, S.T. Frandsen, K. Hansen, J.G. Schepers, K. Rados,W. Schlez, A. Neubert, L.E. Jensen, and S. Neckelmann, “Modelling the impact of wakes on power output at Nysted and Horns Rev.”, In European Wind Energy Conference, 2009. 4R.J. Barthelmie, S.T. Frandsen, O. Rathmann, K. Hansen, E.S. Politis, J. Prospathopoulos, D. Cabezón, K. Rados, S.P. van der Pijl, J.G. Schepers, W. Schlez, J. Phillips, and A. Neubert, “Flow and wakes in large wind farms in complex terrain and offshore”, In European Wind Energy Conference, 2008. 5Hamada K, Smith TC, Durrani N, Qin N, Howell RJ, “Unsteady flow simulation and dynamic stall around vertical axis wind turbine blades”, AIAA Aerodynamics Conference Reno, 2008. 6Edwards, J., Durrani N., Howell R., Qin N., 2007, “Wind tunnel and numerical study of a small vertical axis wind turbine”, 27th ASME Wind Energy Symposium, AIAA-2008-1316. 7Howell, R., Qin, N., Edwards, J. and Durrani, N., “Wind tunnel and numerical study of a small vertical axis wind turbine”, Renewable Energy, 35 (2). pp. 412-422. ISSN 0960-1481 8Fluent User's Manual, Fluent Inc. (www.fluent.com )