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Abstract:Wind velocity distribution and the vortex around the wind turbine present a significant challenge in the development of straight-bladed vertical axis wind turbines (VAWTs). This paper is intended to investigate influence of tip vortex on wind turbine wake by Computational Fluid Dynamics (CFD) simulations. In this study, the number of blades is two and the airfoil is a NACA0021 with chord length of c = 0.265 m. To capture the tip vortex characteristics, the velocity fields are investigated by the Q-criterion iso-surface (Q = 100) with shear-stress transport (SST) k-ω turbulence model at different tip speed ratios (TSRs). Then, mean velocity, velocity deficit and torque coefficient acting on the blade in the different spanwise positions are compared. The wind velocities obtained by CFD simulations are also compared with the experimental data from wind tunnel experiments. As a result, we can state that the wind velocity curves calculated by CFD simulations are consistent with Laser Doppler Velocity (LDV) measurements. The distribution of the vortex structure along the spanwise direction is more complex at a lower TSR and the tip vortex has a longer dissipation distance at a high TSR. In addition, the mean wind velocity shows a large value near the blade tip and a small value near the blade due to the vortex effect.Keywords: wind energy; vertical axis wind turbine (VAWT); flow field; tip vortex; wind velocity deficit; torque coefficient

In addition, deployment of wind turbines can be a major logistical challenge. The multi-ton products are loaded onto specialized transport trucks (and water service vessels for offshore) and require proper infrastructure, including roadways that are wide enough and foundationally sound enough to support movement of these products to the wind farm site. This is especially true in remote countries like Brazil or India and other areas around the world.

where [C.sub.f] is the capacity coefficient and [P.sub.max] is therated power output for the particular wind turbine. In the simulations, wefocus on [P.sub.max] = 2 MW and [P.sub.max] = 8 MW, which roughly bracketsthe range of potential installations. [C.sub.f] is constrained by both lawsof nature and engineering design. For V < [], the turbine bladesdo not rotate, so [C.sub.f] = 0. Likewise, for V > [V.sub.out] the turbinerotation is halted to avoid damage, and [C.sub.f] = 0. As V increases past[], power production rises rapidly, but by engineering design isbrought to a broad plateau of [P.sub.max], by mechanical adjustment of theturbine blade pitch angle [6].

At large Reynolds number, [C.sub.t] is predominantly shapedependent. For example, there are many references giving values such as for aflat plate [C.sub.t] = 1.28 and for a sphere [C.sub.t] = 0.47. The drag forcefor rotating turbine blades is much greater than a calculation based onstationary blades and using just the area presented by the blades. The dragforce of the wind turbine is characterized in terms of the disk swept out, A= [pi][R.sup.2], where R is blade length. For the Bonus Energy A/S 2.0 MW,[C.sub.t] peaks at approximately [C.sub.t] = 0.88 [2]. Presumably this citedvalue of [C.sub.t] includes the drag of the tower as well, but in thisparameterization the drag force is modeled as occurring within the area ofthe rotor.

In the above estimates, what value should be used for H Also,what is the contribution of transport through the top of the wind farm Wealso need to recognize that as the power extraction approaches the upperlimit, that would imply that V would be decreasing as the wind farm istraversed. The continuity equation would thus require upward advection ofenergy out of the top of the wind farm. All these considerations imply that amore refined estimate of the limits to power extraction at a site willrequire details about the wind climate, including boundary layer mixing, aswell as the use of a numerical weather prediction model.

Consider increasing CD from 2.5 W [m.sup.-2], with 2 MW turbines,to 10 W [m.sup.-2] by either quadrupling the area of the rotors orquadrupling the number of turbines. The two scenarios can be found withinFigure 8. Increasing the rotor area density by a factor of 4 (redeploying as8 MW turbines) increased PD by 2.07. Quadrupling the number of 2 MW turbinesincreased PD by a factor of 1.38. Since the increase in PD was significantlyless than 4, we would say that the collective impact of the turbines on thepower productivity of the winds is significant. Inspection of the winddifference plots in Figure 6 shows wind being reduced above the tops of theturbines, evidently the effect of turbulent transport of momentum verticallyin the atmosphere. This transport may be hard to estimate by means other thana detailed numerical model. 59ce067264


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