Wind tunnel and numerical study of a straight-bladed vertical axis wind turbine in three-dimensional analysis (Part I: For predicting aerodynamic loads and performance)

Li, Qingan; Maeda, Takao; Kamada, Y.; Murata, Junsuke; Kawabata, Toshiaki; Shimizu, Kento; Ogasawara, Tatsuhiko; Nakai, Alisa; Kasuya, Takuji

doi:10.1016/j.energy.2016.03.089

Cited by 83 publications

(41 citation statements)

References 31 publications

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“…It is considered that the influence of the blade vortex is greater when close to the tip of blade. Li et al [29] in 2016 also obtained the similar results with the LDV measurement in a large wind tunnel. Figure 10 illustrates the low wind velocity contours in different cross-sections of l = 0, 0.25, 0.50 and 0.75 when the azimuth angle is θ = 90 • .…”

Section: Resultssupporting

confidence: 75%

“…The torque coefficient C Q of the rotor which reflects the wind turbine performance can be expressed as [16,29,39]:…”

Section: Data Processing Methodsmentioning

confidence: 99%

“…As previously mentioned, [15,29] Li et al measured the wind velocity around the wind turbine by using LDV system. However, it is still very difficult to fully understand the evolution of the vortex field due to limitations of the experimental technology.…”

Section: Introductionmentioning

confidence: 99%

“…In their study, the rotor aspect ratio was only affected by the airflow near the blade tip. In addition, in 2016 Li et al [28,29] discussed the influence of the shedding vortex of blade on the flow field around blade by using LDV system. The results suggested that the wind velocity in the surface of the blade increased and the differential pressure in the surface of the blade decreased as it went away from the center along the spanwise direction.…”

Section: Introductionmentioning

confidence: 99%

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Numerical Investigation of the Tip Vortex of a Straight-Bladed Vertical Axis Wind Turbine with Double-Blades

et al. 2017

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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.

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Section: Resultssupporting

confidence: 75%

“…The torque coefficient C Q of the rotor which reflects the wind turbine performance can be expressed as [16,29,39]:…”

Section: Data Processing Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Numerical Investigation of the Tip Vortex of a Straight-Bladed Vertical Axis Wind Turbine with Double-Blades

et al. 2017

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“…Further, the lift coefficient CL and the drag coefficient CD are obtained by the non-dimensional lift force FL and drag force FD per unit blade as determined by equations (1) and (2) from the dynamic pressure and chord length c. They are given by the following equations: Maeda et al, 2012) and Li (Li et al, 2015(Li et al, , 2016b(Li et al, , 2016c(Li et al, , 2016d.…”

Section: Non-dimensional Lift and Dragmentioning

confidence: 99%

Experimental investigation of load fluctuation on horizontal axis wind turbine for extreme wind direction change

Sang

Murata

Morimoto

et al. 2017

JFST

Self Cite

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The operating conditions of Horizontal Axis Wind Turbine (HAWT) are extremely complex in natural surroundings. One of the wind conditions is called extreme wind direction change which has been specified in the International Electrotechnical Commission (IEC) 61400-1 standard. External conditions can generate extreme loads which may affect the power coefficient and the lifetime of HAWTs. This paper attempted to compile the evaluation of the aerodynamic forces acting on a small HAWT under extreme wind direction change condition in the wind tunnel experiments. An Avistar airfoil is used for the two-bladed and three-bladed wind turbines. This study is intended to clarify the load fluctuation when sudden wind direction change reacts to two-bladed and three-bladed wind turbines. A vane system is used to generate the wind direction change. A 6-component balance is used to measure the forces and the moments acting on the entire wind turbine in the three directions of x, y and z-axes. The results show that when the extreme wind direction change is generated, the yaw moment fluctuation amplitude of two-bladed wind turbine is about 39% larger than that of the three-bladed one. The strong dependence of the inflow timing of the wind direction change on the fluctuation amplitude can be seen only for the two-bladed wind turbine.

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A Novel Surrogated Approach for Optimizing a Vertical Axis Wind Turbine With Straight Blades

Sanaye,

Rezaeian,

Farvizi

2024

Wind Energy

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Vertical axis wind turbine (VAWT) has a rotating axis perpendicular to the wind direction. This type of wind turbine that is suitable for urban environments has low wind direction dependency and noise. In this research, a novel surrogated approach for optimizing a VAWT is proposed, used, tested, and verified, which is not reported in literature. The proposed method consisted of 3D computational fluid dynamics (CFD) analysis of wind flow through the wind turbine with FLUENT software by solving the unsteady turbulent equations. However, 3D CFD analysis was time and cost consuming to obtain the output result (power coefficient) from input values (airfoil chord length, pitch angle, and tip speed ratio as turbine design variables). Thus, artificial neural network (ANN) was applied to obtain weight functions to correlate FLUENT software inputs and outputs after learning process. Finally, genetic algorithm was used for maximizing the turbine power coefficient considering three defined design variables. The optimum value of power coefficient was improved to 0.244, and the optimum values of design variables for blade chord length, blade pitch angle, and blade tip speed ratio were 0.218, −0.453, and 1.24, respectively. This novel surrogated method reduced the computational time and cost of VAWT optimizing considerably.

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Wind tunnel and numerical study of a straight-bladed vertical axis wind turbine in three-dimensional analysis (Part I: For predicting aerodynamic loads and performance)

Cited by 83 publications

References 31 publications

Numerical Investigation of the Tip Vortex of a Straight-Bladed Vertical Axis Wind Turbine with Double-Blades

Numerical Investigation of the Tip Vortex of a Straight-Bladed Vertical Axis Wind Turbine with Double-Blades

Experimental investigation of load fluctuation on horizontal axis wind turbine for extreme wind direction change

A Novel Surrogated Approach for Optimizing a Vertical Axis Wind Turbine With Straight Blades

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