Large-eddy simulation and experimental study on the turbulent wake flow characteristics of a two-bladed wind turbine

Luo, Kun; Yuan, Renyu; Dong, Xueqing; Wang, Jianwen; Zhang, Sanxia; Fan, Jianren; Ni, Mingjiang; Cen, Kefa

doi:10.1007/s11431-017-9109-7

Cited by 9 publications

(3 citation statements)

References 35 publications

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“…In studies focusing on series arrangements, Dou et al [19] experimented by adjusting the streamwise spacing between upstream and downstream turbines, concluding that increasing the spacing accelerates wake recovery. The interaction between wakes from multiple turbines is a crucial factor, as shown in Luo et al's research [22], which simulated turbine wakes and structures and indicated that downstream turbines are still affected by wake effects in the far wake region. In the literature, a study by Allah et al [23] confirms that the blending of upstream and downstream multiple wind turbine wake streams can promote the recovery of wind turbine wake streams.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

Zhang,

Feng,

Zhao

et al. 2024

JMSE

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During the expansion of a wind farm, the strategic placement of wind turbines can significantly improve wind energy utilization. This study investigates the evolution of wake turbulence in a wind farm after introducing smaller wind turbines within the gaps between larger ones, focusing on aspects such as wind speed, turbulence intensity, and turbulence integral length scale. The flow field conditions are described using parameters like turbulence critical length and power spectral density, as determined through wind tunnel experiments. In these experiments, a single large wind turbine model and nine smaller wind turbine models were used to create a small wind farm unit, and pressure distribution behind the wind turbines was measured under various operating conditions. The results indicate that downstream wind speed deficits intensify as the number of small wind turbines in operation increases. The impact of these smaller turbines varies with height, with a relatively minor effect on the upper blade tip and increasingly adverse effects as you move from the upper blade tip to the lower blade tip. Through an analysis of power spectral density, the contribution of vortex motion to wake turbulence kinetic energy is further quantified. In the far wake region, the number of small wind turbines has a relatively small impact on wind speed fluctuations.

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Section: Introductionmentioning

confidence: 99%

Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

Zhang,

Feng,

Zhao

et al. 2024

JMSE

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“…Compared with the traditional two-dimensional PIV technique, TR-PIV technology has a high spatial and temporal resolution, which is suitable for measuring the dynamic parameters of an unsteady flow field, such as Reynolds stress, turbulent intensity, and turbulent kinetic energy. Therefore, the TR-PIV technology is applicable to wake turbulence and other complex flow measurements [31,32], moreover, it can effectively reveal the transient characteristics of the blade tip vortex [33,34]. Furthermore, it can determine the spatial correlation of the wake structure.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Turbulence Intensity and Tip Speed Ratio on the Coherent Structure of Horizontal-Axis Wind Turbine Wake: A Wind Tunnel Experiment

Han¹,

Wang²,

Li³

et al. 2022

Energy Engineering

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The evolution laws of the large-eddy coherent structure of the wind turbine wake have been evaluated via wind tunnel experiments under uniform and turbulent inflow conditions. The spatial correlation coefficients, the turbulence integral scales and power spectrum are obtained at different tip speed ratios (TSRs) based on the timeresolved particle image velocity (TR-PIV) technique. The results indicate that the large-eddy coherent structures are more likely to dissipate with an increase in turbulence intensity and TSR. Furthermore, the spatial correlation of the longitudinal pulsation velocity is greater than its axial counterpart, resulting into a wake turbulence dominated by the longitudinal pulsation. With an increase of turbulence intensity, the integral scale of the axial turbulence increases, meanwhile, its longitudinal counterpart decreases. Owing to an increase in TSR, the integral scale of axial turbulence decreases, whereas, that of the longitudinal turbulence increases. By analyzing the wake power spectrum, it is found that the turbulent pulsation kinetic energy of the wake structure is mainly concentrated in the low-frequency vortex region. The dissipation rate of turbulent kinetic energy increases with an increase of turbulence intensity and the turbulence is transported and dissipated on a smaller scale vortex, thus promoting the recovery of wake.

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“…After an upstream wind turbine extracts kinetic energy from wind, it propagates towards downstream wind direction forming a large wake area characterized with lower wind speed and more intensive wind turbulence. This is called the wake effect [1]. When another wind turbine is located inside the wake-affected zone, its power output will be reduced to a large extent with a high fatigue load [2].…”

Section: Introductionmentioning

confidence: 99%

Optimal Irregular Wind Farm Design for Continuous Placement of Wind Turbines with a Two-Dimensional Jensen-Gaussian Wake Model

Wang

Zhou

2018

Applied Sciences

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Optimal design of wind turbine placement in a wind farm is one of the most effective tools to reduce wake power losses by alleviating the wake effect in the wind farm. In comparison to the discrete grid-based wind farm design method, the continuous coordinate method has the property of continuously varying the placement of wind turbines, and hence, is far more capable of obtaining the global optimum solutions. In this paper, the coordinate method was applied to optimize the layout of a real offshore wind farm for both simplified and realistic wind conditions. A new analytical wake model (Jensen-Gaussian model) taking into account the wake velocity variation in the radial direction was employed for the optimization study. The means of handling the irregular real wind farm boundary were proposed to guarantee that the optimized wind turbine positions are feasible within the wind farm boundary, and the discretization method was applied for the evaluation of wind farm power output under Weibull distribution. By investigating the wind farm layout optimization under different wind conditions, it showed that the total wind farm power output increased linearly with an increasing number of wind turbines. Under some particular wind conditions (e.g., constant wind speed and wind direction, and Weibull distribution), almost the same power losses were obtained under the wake effect of some adjacent wind turbine numbers. A common feature of the wind turbine placements regardless of the wind conditions was that they were distributed along the wind farm boundary as much as possible in order to alleviate the wake effect.

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Large-eddy simulation and experimental study on the turbulent wake flow characteristics of a two-bladed wind turbine

Cited by 9 publications

References 35 publications

Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

Experimental Study of Wake Evolution under Vertical Staggered Arrangement of Wind Turbines of Different Sizes

The Effects of Turbulence Intensity and Tip Speed Ratio on the Coherent Structure of Horizontal-Axis Wind Turbine Wake: A Wind Tunnel Experiment

Optimal Irregular Wind Farm Design for Continuous Placement of Wind Turbines with a Two-Dimensional Jensen-Gaussian Wake Model

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