Towards physics-based operational modeling of the unsteady wind turbine response to atmospheric and wake-induced turbulence

Marichal, Yves; Visscher, Ivan De; Chatelain, Philippe; Winckelmans, Grégoire

doi:10.1088/1742-6596/854/1/012030

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…Those techniques have been successfully applied to detect wake characteristics on velocity fields from Large Eddy Simulations (LES) under uniform and ABL flows, and some techniques have been found to be robust for aligned wind turbines immersed in upstream wakes or for side-by-side interacting wakes configurations [1,4]. The description of the wake centre, width or velocity deficit from high-fidelity LES models are relevant data for calibrating engineering models [6,7] or mid-fidelity simulations [8,9,10]. A methodology was proposed to calibrate the medium fidelity and high-fidelity LES tools by minimizing the error on the wake centre lateral displacement probability density functions, and radial velocity profiles within the wakes [11,12].…”

Section: Introductionmentioning

confidence: 99%

Wake structure analysis of a wind turbine under various atmospheric flow conditions and its application for mid-fidelity calibration

Euzenat,

Baiza Martinez,

et al. 2024

J. Phys.: Conf. Ser.

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A coupled Actuator Line Method (ALM) Large Eddy Simulation (LES) is used to simulate the wake structure of an isolated wind turbine. The wake centre position, boundary, and dynamics downstream of the wind turbine is determined under different atmospheric flow conditions, including neutral, stable, and unstable stratification. The wake centre lateral displacement and autocorrelation are seen to be affected by the atmospheric flow conditions. Finally, the instantaneous wake structure is then used as reference to improve the accuracy of mid-fidelity approach.

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Section: Introductionmentioning

confidence: 99%

Wake structure analysis of a wind turbine under various atmospheric flow conditions and its application for mid-fidelity calibration

Euzenat,

Baiza Martinez,

et al. 2024

J. Phys.: Conf. Ser.

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Development of wake meandering detection algorithms and their application to large eddy simulations of an isolated wind turbine and a wind farm

Coudou

Moens

Marichal³

et al. 2018

J. Phys.: Conf. Ser.

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Data assimilation for the prediction of wake trajectories within wind farms

Lejeune

Moens

Coquelet

et al. 2020

J. Phys.: Conf. Ser.

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In this paper, we formulate a physics-based surrogate wake model in the framework of online wind farm control. A flow sensing module is coupled with a wake model in order to predict the behavior of the wake downstream of a wind turbine based on its loads, wind probe data and operating settings. Information about the incoming flow is recovered using flow sensing techniques and then fed to the wake model, which reconstructs the wake based on this limited set of information. Special focus is laid on limiting the number of input parameters while keeping the computational cost low in order to facilitate the tuning procedure. Once calibrated, comparison with high-fidelity numerical results retrieved from Large Eddy Simulation (LES) of a wind farm confirms the good potential of the approach for online wake prediction within farms. The two approaches are further compared in terms of their wake center and time-averaged speed deficit predictions demonstrating good agreement in the process.

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Towards physics-based operational modeling of the unsteady wind turbine response to atmospheric and wake-induced turbulence

Cited by 3 publications

References 11 publications

Wake structure analysis of a wind turbine under various atmospheric flow conditions and its application for mid-fidelity calibration

Wake structure analysis of a wind turbine under various atmospheric flow conditions and its application for mid-fidelity calibration

Development of wake meandering detection algorithms and their application to large eddy simulations of an isolated wind turbine and a wind farm

Data assimilation for the prediction of wake trajectories within wind farms

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