A novel three-dimensional wake model based on anisotropic Gaussian distribution for wind turbine wakes

He, Ruiyang; Yang, Hongxing; Sun, Haiying; Gao, Xiaoxia

doi:10.1016/j.apenergy.2021.117059

Cited by 48 publications

(9 citation statements)

References 25 publications

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“…We assumed that the wake velocity distribution at the uniform inflow satisfies a Gaussian function (shown in Figure 2a) and can be expressed as 33 :…”

Section: Development Of the Present 3dg-k Wake Modelmentioning

confidence: 99%

“…Ishihara and Qian 32 introduced a Gaussian model based on LES data to enhance the predictive accuracy of the near wake region in the Bastankhah and Porté-Agel model. In their initial work, He et al 33 proposed a 3D wake model that employed a multivariate…”

Section: Introductionmentioning

confidence: 99%

“…Ishihara and Qian 32 introduced a Gaussian model based on LES data to enhance the predictive accuracy of the near wake region in the Bastankhah and Porté‐Agel model. In their initial work, He et al 33 proposed a 3D wake model that employed a multivariate Gaussian distribution and provided an expression for the wake expansion rate in each dimension. This model underwent validation in four specific cases.…”

Section: Introductionmentioning

confidence: 99%

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A three‐dimensional analytical model based on Gaussian distribution for wind‐turbine wakes

Ling,

Zhao,

Liu

et al. 2023

Env Prog and Sustain Energy

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A Gaussian‐shaped, three‐dimensional (3DG‐k) wake model is proposed considering the shear wind effect. The model defines the wake radius rw to be equal to twice the Gaussian standard deviation σ and establishes a link with the expansion coefficient k of the physical wake boundary to describe the wake boundary. Garrad Hassan (GH) wind tunnel test data, Shiren wind farm measurement data, Nibe wind farm measurement data, and Vestas V80‐2MW wind turbine computational data by large eddy simulation method are used to validate the accuracy of the 3DG‐k, Jensen, 3D Gaussian (3DG), and 3D cosine (3D‐C) models. Results show that the 3DG‐k model exhibits higher accuracy for the four cases compared to other models. Due to its simplicity and universality, the model can be used for layout optimization and wake control of wind farms.

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“…We assumed that the wake velocity distribution at the uniform inflow satisfies a Gaussian function (shown in Figure 2a) and can be expressed as 33 :…”

Section: Development Of the Present 3dg-k Wake Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A three‐dimensional analytical model based on Gaussian distribution for wind‐turbine wakes

Ling,

Zhao,

Liu

et al. 2023

Env Prog and Sustain Energy

View full text Add to dashboard Cite

show abstract

“…In the 2D Gaussian model of Xiaoxia et al (Jensen‐Gaussian model) 9 that was obtained by coupling the Jensen's wake model and the Gaussian equations, incorporation of the wake turbulence in the model improved its accuracy. A later improvement of this 2D model into a 3D one was obtained by inclusion of a modified anisotropic

k_{w} .

10 As other examples of 3D analytical models one can point out (i) the model of Ishihara and Qian, 15 which included incorporation of the turbulence by a new mathematical approach, (ii) the model of Sun and Yang, 29 which utilized momentum conservation and an isotropic

k_{w}

, and (iii) the model of He et al, 30 which employed an anisotropic

k_{w}

and took into account the free stream wind shear effect by using mass conservation law. In our previous work, 27 we proposed a new 2D analytical model based on coupling Jensen's wake model and the Gaussian function by adopting a more realistic control volume to calculate the wake initial radius at formation, and provided a modified expression for computation of

k_{normalw, rev}

.…”

Section: Introductionmentioning

confidence: 99%

A 3D analytical model for predicting horizontal‐axis wind turbines wake based on a 2D analytical wake model

Ayoubi

Yazdi

Harsini

2022

Env Prog and Sustain Energy

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The development of easy-to-implement 3D analytical models of the wake is highly desirable, due to the critical role played by the prediction of the wake velocity profile in the estimation of power generation and the layout optimization of wind turbines in wind farms. Herein, a 3D analytical model of the wake (based on a 2D analytical model) has been proposed, which is easy to implement thanks to using the Gaussian function for the description of the velocity profile and assuming an isotropic value for the wake decay coefficient. Validation of the model was carried out using six cases of wind tunnel, field measurement, and simulation data in horizontal and vertical planes, where the model was compared with three 3D analytical models of the literature. The predictions of the model for the normalized wind velocity typically exhibited mean absolute percentage error (MAPE) values of MAPE ≤3 at downwind distances of x ≥ d t (d t is the rotor diameter), which are the economically-and power harvesting-optimized inter-turbine spacing in wind farms. In addition to its theoretical significance, the model bears utility potentials in applications concerning solving practical problems in wind farms.

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“…Furthermore, the authors have measured equivalent inflow wind speed via the wake superposition model. He et al (2021) have used multivariate Gaussian distribution to present a more advanced three-dimensional wake model for wind power generation to estimate the vertical wake profile (He et al, 2021). Gao et al (2020) have proposed a three-dimensional Jensen-Gaussian for the wake profile of HAWT, which accounts for the wind shear effect and the difference between wind-shear inflow wind speed and uniform inflow wind speed.…”

Section: Introductionmentioning

confidence: 99%

Wake reduction in horizontal axis wind turbine: A review of advancements in techniques

Awan

Sarosh

2022

Wind Engineering

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Renewable energy systems have experienced exponential growth toward producing zero-carbon energy. In this context, wind turbines continue to play a significant role. To extract maximum power, wind turbines are installed in array-like formation in wind farms. This arrangement though beneficial, also leads to detrimental wind-wakes effects. The wakes reduce wind speed and induce undesirable turbulence of flow field in downstream direction. To address this issue, several innovative techniques have been proposed. This paper surveys the best methods by classifying these into passive and active techniques. The passive techniques affect the wake flow by modifying only the geometrical or operating characteristics of wind turbines such as adjustment of forward and backward sweeps, etc. The active techniques use additional surfaces/devices for wake handling such as vortex generators, leading edge protuberances, dual-rotors, and cross-axis wind turbines etc. Additionally, this paper also reviews various wake measurement methods and recommends the best suited technique.

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A novel three-dimensional wake model based on anisotropic Gaussian distribution for wind turbine wakes

Cited by 48 publications

References 25 publications

A three‐dimensional analytical model based on Gaussian distribution for wind‐turbine wakes

A three‐dimensional analytical model based on Gaussian distribution for wind‐turbine wakes

A 3D analytical model for predicting horizontal‐axis wind turbines wake based on a 2D analytical wake model

Wake reduction in horizontal axis wind turbine: A review of advancements in techniques

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