Prediction of wind‐turbine fatigue loads in forest regions based on turbulent LES inflow fields

Nebenführ, Bastian; Davidson, Lars

doi:10.1002/we.2076

Cited by 26 publications

(28 citation statements)

References 32 publications

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“…The source term for the dissipation,

ϵ

, is,

f_{ϵ} = ρ C_{d} α_{f} false| U false| ϵ ([], \frac{C_{ϵ 4} β_{p} false| U {false|}^{2}}{k} - C_{ϵ 5} β_{d}),

where

C_{ϵ 4} = 0.9

and

C_{ϵ 5} = 0.9

are model constants. Desmond et al and some others have used this model and it has been verified as an accurate assessment of the porosity of the forest canopy . The choice of values of the coefficients in the source terms equations are adopted from references …”

Section: Modelling Approachesmentioning

confidence: 99%

“…Desmond et al and some others have used this model and it has been verified as an accurate assessment of the porosity of the forest canopy . The choice of values of the coefficients in the source terms equations are adopted from references …”

Section: Modelling Approachesmentioning

confidence: 99%

“…Series of numerical studies have been carried out on the simulations of wind flow over forest . In most of these studies, the forest canopy features have been explicitly represented in the simulation domain using the leaf area density (LAD).…”

Section: Introductionmentioning

confidence: 99%

“…There have been very few studies so far that investigated the effects of forests on a wind turbine. Nebenführ and Davidson investigated the ABL over a sparse and a dense forest, as well as over grass‐covered flat terrain . They studied the impact of two different forests and wind speed on the wind‐turbine fatigue loads.…”

Section: Introductionmentioning

confidence: 99%

“…The studied forest is a Scots pine ( Pinus sylvestris ) with densities varying from an extremely sparse (LAI

= 0.42

) to an extremely dense (LAI

= 8.5

) forest. Also, following previous studies, in which ABL flows over forest has been simulated, we assume each forest case to be homogeneous in the horizontal directions but the LAD is varying in the vertical direction. The numerical simulations have been carried out using the open‐source code OpenFOAM .…”

Section: Introductionmentioning

confidence: 99%

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Impact of different forest densities on atmospheric boundary‐layer development and wind‐turbine wake

2020

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The aim of this work is to investigate the atmospheric boundary-layer (ABL) flow and the wind turbine wake over forests with varying leaf area densities (LAD). The forest LAD profile used in this study is based on a real forest site, Ryningsnäs, located in Sweden. The reference turbine used to model the wake is a well-documented 5-MW turbine, which is implemented in the simulations using an actuator line model (ALM). All simulations are carried out with openFOAM using the Reynolds averaged Navier-Stokes (RANS) approach. Twelve forest cases with leaf area index (LAI) ranging from 0.42 to 8.5 are considered. Results show that the mean velocity decreases with increasing LAI within the forest canopy, but increases with LAI above the hub height. Meanwhile, the turbulent kinetic energy (TKE) varies nonmonotonically with forest density. The TKE increases with forest density and reaches to its maximum at an average LAI of 1.70, afterwards, it decreases gradually as the density increases. It is also observed that the forest density has a clear role in the wake development and recovery. Comparisons between no-forest and forest cases show that the forest characteristics help in damping the added turbulence from the turbine. As a consequence, the forest with the highest upstream turbulence has the shortest wake downstream of the turbine. KEYWORDS actuator line model, atmospheric boundary-layer, forest density, turbulent kinetic energy, wind power, wind-turbine wake

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“…The source term for the dissipation,

ϵ

, is,

f_{ϵ} = ρ C_{d} α_{f} false| U false| ϵ ([], \frac{C_{ϵ 4} β_{p} false| U {false|}^{2}}{k} - C_{ϵ 5} β_{d}),

where

C_{ϵ 4} = 0.9

and

C_{ϵ 5} = 0.9

Section: Modelling Approachesmentioning

confidence: 99%

Section: Modelling Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…The studied forest is a Scots pine ( Pinus sylvestris ) with densities varying from an extremely sparse (LAI

= 0.42

) to an extremely dense (LAI

= 8.5

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Impact of different forest densities on atmospheric boundary‐layer development and wind‐turbine wake

2020

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Numerical simulations of fatigue loads on wind turbines operating in wakes

Liu

Ishihara

et al. 2020

Wind Energy

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Wake effects increase the fatigue loads on wind turbines in operation. However, the wake flow is considerably different from the traditional boundary layer flow, and poses many challenges in determining the fatigue loads on wind turbines operating in a wake. Therefore, in the present study, the actuator-line model was adopted to numerically simulate the wake flow and an in-house code named AOWT, which is based on a generalized coordinate method, was developed for analyzing the dynamics of wind turbines under an arbitrary distribution of the turbulent flow field varying in time and space. Using the numerically modeled instantaneous wake flow fields and AOWT, the dynamic response of a wind turbine, located at specified positions in both tandem and staggered arrangements in a wake, was examined, and the fatigue loads were determined. Furthermore, to determine the major contributions to the fatigue loads, the loads induced by the spatial variation of the mean flow fields were predicted. To the best of the authors' knowledge, no such analysis has been conducted thus far. Importantly, it was found that in the near-wake region, the mean flow field had a significant influence on the fatigue loads, especially in the staggered layout. However, there is no analytical wake model available in the literature capable of predicting the near-wake mean flow fields. Therefore, in this study, a near-wake model was proposed, which yielded satisfactory predictions of the mean velocities in the near-wake region. K E Y W O R D Sblade element method, dynamic response, fatigue load, LES, wake flow, wake model | INTRODUCTIONWind turbines are usually installed as wind farms, in which the upstream wind turbines disturb the upcoming flow field and increase the downstream turbulence. 1-7 Consequently, the fatigue loads on the downstream wind turbines owing to the wake effects are different from those created by a traditional boundary layer flow. 8,9 A method using the effective turbulence intensity 10,11 has been commonly employed to assess the wake effects on the fatigue loads on wind turbines. However, the flow field in a wake is strongly distorted in terms of both the turbulence intensity and the mean flow. As a result, detailed examinations of the wake effects on the fatigue loads are needed. Whereas, the researches 12-15 considering this issue are not as many as those about the fatigue loads induced by the traditional boundary layer. [16][17][18][19][20] This could be owing to the fact that the wind turbine wake flow is much different with the traditional boundary layer flow, failing the applications of the conventional approaches for the turbulent flow generations, 11,21 posing many challenges in determining the fatigue loads on a wind turbine operating in wakes. In recent years, the engineering models, such as

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Multiscale modeling of the atmospheric environment over a forest canopy

Yan

Miao

Liu

et al. 2020

Sci. China Earth Sci.

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Vegetation constitutes one of the fundamental types of land use on Earth. The presence of trees in urban areas can decrease local winds and exchange sensible and latent heat with the surrounding environments, thus exerting notable influences on the urban microenvironment. A better understanding of the turbulent transfer of momentum and scalars around vegetation canopy could significantly contribute to improvement of the urban environment. This work develops a large-eddy simulation (LES) method that is applicable to model the flow and scalar transport over the forest canopy. We study the atmospheric flow over complex forested areas under typical weather conditions by coupling LES to the mesoscale model. Models of radiation and energy balance have been developed with explicit treatment of the vegetation canopy. By examining the flow over a forest canopy under a range of stability conditions, we found that buoyancy enhances or suppresses turbulent mixing in unstable or stable atmosphere respectively, with decreasing or increasing wind shear, respectively. From the multiscale modeling of the Beijing Olympic Forest Park, the present coupling scheme proves to better resolve the diurnal variations in wind speed, temperature, and relative humidity over complex urban terrains. The coupling scheme is superior to the traditional mesoscale model in terms of wind field simulation. This is mainly because the coupling scheme not only takes the influences of external mesoscale flow into consideration, but also resolves the heterogeneous urban surface at a fine scale by downscaling, thus better reproducing the complex flow and turbulent transport in the urban roughness sublayer.

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Prediction of wind‐turbine fatigue loads in forest regions based on turbulent LES inflow fields

Cited by 26 publications

References 32 publications

Impact of different forest densities on atmospheric boundary‐layer development and wind‐turbine wake

Impact of different forest densities on atmospheric boundary‐layer development and wind‐turbine wake

Numerical simulations of fatigue loads on wind turbines operating in wakes

Multiscale modeling of the atmospheric environment over a forest canopy

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