Brief communication: A double-Gaussian wake model

Schreiber, Johannes; Balbaa, Amr; Bottasso, Carlo L.

doi:10.5194/wes-5-237-2020

Cited by 41 publications

(49 citation statements)

References 12 publications

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“…Figure 13 reports horizontal and vertical profiles of normalized velocity deficit for the laminar and uniform TUM-LT and sheared and turbulent TUM-HT conditions. Results for the TUM-LT inflow conditions reveal, especially for the horizontal scan, the typical double-Gaussian profile in the near wake (Schreiber et al, 2020a). As expected, in the TUM-HT case the higher TI accelerates the dissipation of the nacelle wake, resulting in a single-Gaussian profile (Bastankhah and Porté-Agel, 2017a;Vermeer et al, 2003).…”

Section: Velocity Deficit Recovery and Wake Deflectionsupporting

confidence: 67%

Design, performance and wake characterization of a scaled wind turbine with closed-loop controls

Nanos¹,

Bottasso²,

Campagnolo³

et al. 2021

Preprint

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Abstract. This paper describes the design and characterization of a scaled wind turbine model, conceived to support wake and wind farm control experiments in a boundary layer wind tunnel. The turbine has a rotor diameter of 0.6~meters, and was designed to match the circulation distribution of a target conceptual full-scale turbine at its design tip speed ratio. In order to enable the testing of plant-level control strategies, the model is equipped with closed-loop pitch, torque and yaw control, and is sensorized with integrated load cells, as well as with rotor azimuth and blade pitch encoders. After describing the design of the turbine, its performance and wake characteristics are assessed by conducting experiments in two different wind tunnels, in laminar and turbulent conditions, collecting wake data with different measurement techniques. A large-eddy simulator coupled to an actuator-line model is used to develop a digital replica of the turbine and of the wind tunnel. For increased accuracy, the polars of the low-Reynolds airfoil used in the numerical model are tuned directly from measurements obtained from the rotor in operation in the wind tunnel. Results indicate that the scaled turbine performs as expected, measurements are repeatable and consistent, and the wake appears to have a realistic behavior in line with expectations and with a similar slightly larger scaled model turbine. Furthermore, the predictions of the numerical model are well in line with experimental observations.

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Section: Velocity Deficit Recovery and Wake Deflectionsupporting

confidence: 67%

Design, performance and wake characterization of a scaled wind turbine with closed-loop controls

Nanos¹,

Bottasso²,

Campagnolo³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The idea of using a super-Gaussian shape function has already been suggested in Shapiro et al (2019). In the present work, an alternative formulation is presented.…”

Section: Introductionmentioning

confidence: 99%

“…Another velocity deficit distribution has been proposed by Keane et al (2016) and Schreiber et al (2020): their model is derived by applying conservation of mass and momentum in the context of actuator disk theory but assumes a distribution of the double-Gaussian type for the velocity deficit in the wake. Indeed, the authors consider that the near wake is better approximated using a double-Gaussian distribution.…”

Section: Introductionmentioning

confidence: 99%

“…In the present work, an alternative formulation is presented. Both mass and momentum are conserved following the derivation of the Gaussian model of Bastankhah and Porté-Agel (2014), whereas in the work of Shapiro et al (2019), only mass conservation is enforced. Furthermore, a new form of the nearwake correction for the velocity deficit proposed by Qian and Ishihara (2018) is presented, and an analytical expression for the evolution of the super-Gaussian order n as a function of the downstream distance is proposed.…”

Section: Introductionmentioning

confidence: 99%

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An alternative form of the super-Gaussian wind turbine wake model

Blondel

Cathelain

2020

Wind Energ. Sci.

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Abstract. A new analytical wind turbine wake model, based on a super-Gaussian shape function, is presented. The super-Gaussian function evolves from a nearly top-hat shape in the near wake to a Gaussian shape in the far wake, which is consistent with observations and measurements of wind turbine wakes. Using such a shape function allows the recovery of the mass and momentum conservation that is violated when applying a near-wake regularization function to the expression of the maximum velocity deficit of the Gaussian wake model. After a brief introduction of the theoretical aspects, an easy-to-implement model with a limited number of parameters is derived. The super-Gaussian model predictions are compared to wind tunnel measurements, full-scale measurements, and a large-eddy simulation (LES), showing a good agreement and an improvement compared with predictions based on the Gaussian model.

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“…Further, in order to obtain a consistent estimate of the advection velocity, ũW i (t), in the nearwake region and hence of the wake deflection, z c (x, t), a near-wake correction strategy should be considered. This issue is addressed by different authors who introduced new speed deficit parametrizations for the near-wake [18,19]. However, for most, these approaches introduce new sets of tuning parameters.…”

Section: Yaw Modelingmentioning

confidence: 99%

Extension and validation of an operational dynamic wake model to yawed configurations

Lejeune

Moens

Chatelain

2022

J. Phys.: Conf. Ser.

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This work extends the capabilities of an operational dynamic wake model to yawed cases. The proposed framework brings together flow sensing and Lagrangian flow modeling into a unified framework: both the freestream flow field and the wake one are discretized as series of information-carrying particles. A source condition for these particles is thus obtained from the wind turbine measurements through flow sensing techniques. The estimated flow field state across the wind farm is finally reconstructed by propagating these particles downstream at their own characteristic velocity. The resulting framework is first presented and its extension to yawed turbine is then discussed. Comparison against high-fidelity Large Eddy Simulations of yawed wind turbines confirms the good potential of the approach: different yaw angles are considered and the performance of the model are evaluated. This study indicates that the proposed framework captures the relevant large scale wake features caused by the combined effect of yawing and wake meandering at a low computational cost thereby making it suitable for online model-based control.

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Brief communication: A double-Gaussian wake model

Cited by 41 publications

References 12 publications

Design, performance and wake characterization of a scaled wind turbine with closed-loop controls

Design, performance and wake characterization of a scaled wind turbine with closed-loop controls

An alternative form of the super-Gaussian wind turbine wake model

Extension and validation of an operational dynamic wake model to yawed configurations

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