Wind-Turbine and Wind-Farm Flows: A Review

Porté‐Agel, Fernando; Bastankhah, Majid; Shamsoddin, Sina

doi:10.1007/s10546-019-00473-0

Cited by 695 publications

(537 citation statements)

References 337 publications

(505 reference statements)

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“…The inflow conditions at different wind speeds, wind shears, and turbulence intensities can lead to considerable influences on the power generation efficiency and wake characteristics of a standalone wind turbine 1–6 . A review study by Porte‐Agel et al 7 summarized the relevant computational, analytical, and experimental research efforts on the interactions of atmospheric boundary layer (ABL) flow with wind turbines and wind farms, with a particular emphasis on our understanding and strategies for modeling the turbine wake flows and their impact on the ABL turbulence structure and wind farm power generation efficiency. According to a real turbine power curve, it is known that an increase of the incoming wind speed can effectively increase the power output of the turbine before reaching the rated capacity 8 .…”

Section: Introductionmentioning

confidence: 99%

Effects of inflow turbulence intensity and turbine arrangements on the power generation efficiency of large wind farms

Lin

Chang

2020

Wind Energy

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In this study, we conduct a series of large-eddy simulations (LESs) to study the impact of different incoming turbulent boundary layer flows over large wind farms, with a particular focus on the overall efficiency of electricity production and the evolution of the turbine wake structure. Five representative turbine placements in the large wind farm are considered, including an aligned layout and four staggered layouts with lateral or vertical offset arrangements. Four incoming flow conditions are used and arranged from the LESs of the ABL flow over homogeneous flat surfaces with four different aerodynamic roughness lengths (i.e., z0 = 0.5, 0.1, 0.01, and 0.0001 m), where the hub-height turbulence intensity levels are about 11.1%, 8.9%, 6.8%, and 4.9%, respectively. The simulation results indicate that an enhancement in the inflow turbulence level can effectively increase the power generation efficiency in the large wind farms, with about 23.3% increment on the overall farm power production and up to about 32.0% increment on the downstream turbine power production. Under the same inflow condition, the change of the turbine-array layouts can increase power outputs within the first 10 turbine rows, which has a maximum increment of about 26.5% under the inflow condition with low turbulence. By comparison, the increase of the inflow turbulence intensity facilitates faster wake recovery that raises the power generation efficiency of large wind farms than the adjustment of the turbine placing layouts. K E Y W O R D Slarge eddy simulation, power output, surface roughness, turbulence intensity, wind farm layout

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Section: Introductionmentioning

confidence: 99%

Effects of inflow turbulence intensity and turbine arrangements on the power generation efficiency of large wind farms

Lin

Chang

2020

Wind Energy

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“…Among a broad spectrum of methods used to study wind turbine wakes [1,2], large-eddy simulation (LES) is a widely-used approach among researchers as it delivers higher fidelity than the Reynolds-averaged Navier-Stokes (RANS) approach. Due to the significant difference in scale between the largest turbulent eddies (∼10 3 m) in the atmospheric boundary layer (ABL) and the chord length of wind turbine blades (1-5 m), it is still computationally too expensive to perform turbine wakes.…”

Section: Introductionmentioning

confidence: 99%

Large-Eddy Simulation of Yawed Wind-Turbine Wakes: Comparisons with Wind Tunnel Measurements and Analytical Wake Models

Lin

Porté‐Agel

2019

Energies

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In this study, we validated a wind-turbine parameterisation for large-eddy simulation (LES) of yawed wind-turbine wakes. The presented parameterisation is modified from the rotational actuator disk model (ADMR), which takes account of both thrust and tangential forces induced by a wind turbine based on the blade-element theory. LES results using the yawed ADMR were validated with wind-tunnel measurements of the wakes behind a stand-alone miniature wind turbine model with different yaw angles. Comparisons were also made with the predictions of analytical wake models. In general, LES results using the yawed ADMR are in good agreement with both wind-tunnel measurements and analytical wake models regarding wake deflections and spanwise profiles of the mean velocity deficit and the turbulence intensity. Moreover, the power output of the yawed wind turbine is directly computed from the tangential forces resolved by the yawed ADMR, in contrast with the indirect power estimation used in the standard actuator disk model. We found significant improvement in the power prediction from LES using the yawed ADMR over the simulations using the standard actuator disk without rotation, suggesting a good potential of the yawed ADMR to be applied in LES studies of active yaw control in wind farms.Energies 2019, 12, 4574 2 of 18 blade-resolved LES of ABL flows through wind turbines [3]. Therefore, most of the LES studies on wind turbine wakes represent the forces induced by wind turbines in ABL flows with various parameterisations.The standard actuator disk model (ADM) without rotation is the simplest wind turbine parameterisation, in which a wind turbine is modelled as a permeable disk with uniformly-distributed normal thrust forces applied on it [4]. A thrust coefficient C T is required by the standard ADM a priori to determine the magnitude of the thrust force. Wu and Porté-Agel [5] later proposed the rotational ADM parameterisation (ADMR), in which the wind turbine thrust and tangential forces are modelled by the blade-element theory. Using aerodynamic and geometric data of the blade as inputs, the ADMR accounts for the wake rotation and non-uniform force distribution on the wind turbine disk. Comparing to the LES results using the standard ADM, Wu and Porté-Agel [5] found that using the ADMR improves the prediction of the main wake flow statistics, such as the mean streamwise velocity and the turbulence intensity.The actuator line model (ALM) parameterisation, developed by Sørensen and Shen [6], was also applied in previous LES studies of wind turbine wakes (e.g., [7][8][9][10]). The ALM represents each blade of a wind turbine as a rotating line source of body forces and computes the corresponding blade-induced forces along the actuator line dynamically in the simulation. As the ALM computes the forces induced by each wind turbine blade, it can resolve more flow structures in the wake, such as tip vortices, than the standard ADM and the ADMR parameterisations. Using the ALM in LES also requires finer mesh resolution and time ste...

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“…Wind turbines in a wind farm can be affected by the wakes generated by upstream wind turbines simultaneously depending on the wind direction. To calculate the wind speed deficit by these multiple wakes, the different superposition methods are available: linear superposition of velocity deficit or energy deficit [37]. In this study the following method based on the conservation of kinetic energy is adopted.…”

Section: Partial and Multiple Wakesmentioning

confidence: 99%

Determining an Appropriate Parameter of Analytical Wake Models for Energy Capture and Layout Optimization on Wind Farms

Yang

2020

Energies

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The wake of a wind turbine is a crucial factor that decreases the output of downstream wind turbines and causes unsteady loading. Various wake models have been developed to understand it, ranging from simple ones to elaborate models that require long calculation times. However, selecting an appropriate wake model is difficult because each model has its advantages and disadvantages as well as distinct characteristics. Furthermore, determining the parameters of a given wake model is crucial because this affects the calculation results. In this study, a method was introduced of using the turbulence intensity, which can be measured onsite, to objectively define parameters that were previously set according to the subjective judgement of a wind farm designer or general recommended values. To reflect the environmental effects around a site, the turbulence intensity in each direction of the wind farm was considered for four types of analytical wake models: the Jensen, Frandsen, Larsen, and Jensen–Gaussian models. The prediction performances of the wake models for the power deficit and energy production of the wind turbines were compared to data collected from a wind farm. The results showed that the Jensen and Jensen–Gaussian models agreed more with the power deficit distribution of the downstream wind turbines than when the same general recommended parameters were applied in all directions. When applied to energy production, the maximum difference among the wake models was approximately 3%. Every wake model clearly showed the relative wake loss tendency of each wind turbine.

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Wind-Turbine and Wind-Farm Flows: A Review

Cited by 695 publications

References 337 publications

Effects of inflow turbulence intensity and turbine arrangements on the power generation efficiency of large wind farms

Effects of inflow turbulence intensity and turbine arrangements on the power generation efficiency of large wind farms

Large-Eddy Simulation of Yawed Wind-Turbine Wakes: Comparisons with Wind Tunnel Measurements and Analytical Wake Models

Determining an Appropriate Parameter of Analytical Wake Models for Energy Capture and Layout Optimization on Wind Farms

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