Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers

Macrì, S.; Aubrun, Sandrine; Leroy, A.; Girard, Nicolas

doi:10.5194/wes-6-585-2021

Cited by 8 publications

(9 citation statements)

References 31 publications

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“…These start times result in advection velocities of U a = 0.81U hub for the descent step and U a = 0.71U hub for the ascent one. These values are close to those reported in [15] for a negative yaw manoeuvre.…”

Section: Metrics For Wake Dynamicssupporting

confidence: 90%

“…These results align those identified in config 1, despite the different inflow conditions. In [15], the authors founded similar values in case of yaw manoeuvres. This result highlights the universality of the advection velocity values in the context of step motions.…”

Section: Metrics For Wake Dynamicsmentioning

confidence: 66%

“…Another study using Doppler lidar experiments showed different results, with advection velocities between 0.7U hub and 0.9U hub [14]. Hot-wire experimentations with a turbine model subjected to yaw manoeuvres were performed in [15]. The results showed that, for a positive yaw manoeuvrei.e.…”

Section: Introductionmentioning

confidence: 98%

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Dynamic response of a wind turbine wake subjected to surge and heave step motions under different inflow conditions

Hubert,

Conan,

Aubrun

2024

J. Phys.: Conf. Ser.

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The development of floating offshore wind turbines poses new challenges since the floating platform introduces complex dynamics in the wind turbine wake. These wake dynamics are intricately tied to the advection velocity, referring to the velocity of the downstream propagation of the air flow, and used in the context of wind farm modelling. The present article investigates the far-wake dynamic response of a wind turbine model subjected to heave (up-down translation) and surge (fore-aft translation) step motions under two distinct inflow conditions. Wind tunnel experiments were conducted with hot-wires in a realistic turbulent inflow and a low shear and no ground effect inflow, achieved by varying the hub height of the wind turbine model in the atmospheric boundary layer developed in the test section. The results show that the dynamic response of the wake under the low shear and no ground effect inflow conditions aligns with a second-order system with the presence of undershoots and overshoots. In contrast, under realistic conditions, it appears like a first-order system with undershoots and overshoots less evident in most cases. Despite these variations the determined advection velocity remains roughly the same and consistent with the literature for both heave and surge step motions, regardless of the inflow conditions.

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Section: Metrics For Wake Dynamicssupporting

confidence: 90%

Section: Metrics For Wake Dynamicsmentioning

confidence: 66%

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Dynamic response of a wind turbine wake subjected to surge and heave step motions under different inflow conditions

Hubert,

Conan,

Aubrun

2024

J. Phys.: Conf. Ser.

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“…( 1) and ( 2) is steady state, which inherently assumes statistically steady-state flow over the time horizon t through t + T . We neglect the wake and rotor dynamics associated with the yaw maneuver (Macrí et al, 2021) and the advection time of the modification to the wake. We account for variations in the wind direction through f (α).…”

Section: Model-based Closed-loop Wake Steering Control Methodology Up...mentioning

confidence: 99%

Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions

et al. 2022

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Abstract. The magnitude of wake interactions between individual wind turbines depends on the atmospheric stability. We investigate strategies for wake loss mitigation through the use of closed-loop wake steering using large eddy simulations of the diurnal cycle, in which variations in the surface heat flux in time modify the atmospheric stability, wind speed and direction, shear, turbulence, and other atmospheric boundary layer (ABL) flow features. The closed-loop wake steering control methodology developed in Part 1 (Howland et al., 2020c, https://doi.org/10.5194/wes-5-1315-2020) is implemented in an example eight turbine wind farm in large eddy simulations of the diurnal cycle. The optimal yaw misalignment set points depend on the wind direction, which varies in time during the diurnal cycle. To improve the application of wake steering control in transient ABL conditions with an evolving mean flow state, we develop a regression-based wind direction forecast method. We compare the closed-loop wake steering control methodology to baseline yaw-aligned control and open-loop lookup table control for various selections of the yaw misalignment set-point update frequency, which dictates the balance between wind direction tracking and yaw activity. In our diurnal cycle simulations of a representative wind farm geometry, closed-loop wake steering with set-point optimization under uncertainty results in higher collective energy production than both baseline yaw-aligned control and open-loop lookup table control. The increase in energy production for the simulated wind farm design for closed- and open-loop wake steering control, compared to baseline yaw-aligned control, is 4.0 %–4.1 % and 3.4 %–3.8 %, respectively, with the range indicating variations in the energy increase results depending on the set-point update frequency. The primary energy increases through wake steering occur during stable ABL conditions in our present diurnal cycle simulations. Open-loop lookup table control decreases energy production in the example wind farm in the convective ABL conditions simulated, compared to baseline yaw-aligned control, while closed-loop control increases energy production in the convective conditions simulated.

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“…As shown in Figure 2, the wind passes through two wind turbines, which are named T1 and T2. T1 extracts wind power, the wind speed behind the wind turbine decreases, and the wind direction changes due to the viscous action between the airflow and blades [29,[50][51][52]; this phenomenon is called the wake effect [53]. In the wake zone, because of the decrease in wind speed and increase in turbulence intensity, the power of T2 decreases and the fatigue damage increases [54].…”

Section: Wake Effect and Wind Energymentioning

confidence: 99%

Progress on Offshore Wind Farm Dynamic Wake Management for Energy

Zhao

Xue

et al. 2022

JMSE

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The wake management of offshore wind farms (OWFs) mainly considers the wake effect. Wake effects commonly occur in offshore wind farms, which cause a 5–10% reduction in power production. Although there have been many studies on wake management, many methods are not accurate enough; for instance, look-up table and static wake model control methods do not consider the time-varying wake state. Dynamic wake management is based on the real-time dynamic wake, so it can increase the energy of the OWFs effectively. For OWFs, dynamic wake control is the main method of dynamic wake management. In this paper, the existing wake model and control progress are discussed, mainly emphasizing the dynamic wake model and the dynamic wake control method, solving the gap of the review for dynamic wake management. This paper presents a digital twins (DT) framework for power and fatigue damage for the first time.. The structure of this paper is as follows: (1) the mechanism of wind farm wake interference is described and then the dynamic wake model is reviewed and summarized; (2) different control methods are analyzed and the dynamic wake management strategies for different control methods are reviewed; (3) in order to solve the problems of dynamic wake detection and real-time effective control, the technology of DT is applied to the dynamic wake control of OWFs. This new DT frame has a promising application prospect in improving power and reducing fatigue damage.

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Experimental investigation of wind turbine wake and load dynamics during yaw maneuvers

Cited by 8 publications

References 31 publications

Dynamic response of a wind turbine wake subjected to surge and heave step motions under different inflow conditions

Dynamic response of a wind turbine wake subjected to surge and heave step motions under different inflow conditions

Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions

Progress on Offshore Wind Farm Dynamic Wake Management for Energy

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