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El-Asha, Said; Li, Zhan; Iungo, Giacomo Valerio

doi:10.1002/we.2037

Cited by 2 publications

(6 citation statements)

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“…High veer (Θ ′ = 0.05 − 0.07 • /m) is observed from 04:00 PM to 04:00 AM (local time) as opposed to the rest of the day (Θ ′ = 0.02 − 0.05 • /m), thus confirming the importance of veer and thermal stratification effects in determining the wind direction profile at different heights [23]. Wind shear is quantified by calibrating the shear exponent (α) over each bin-averaged mean velocity profile according to the following equation [3,25]:…”

Section: Overview Of the Experimental Data Setmentioning

confidence: 68%

“…As wind energy becomes one of the largest renewable energy sources in the United States [1], new challenges of modern wind power plants arise, such as the deployment of wind farms in complex terrain, design and control of turbine rotors able to generate more power even at low wind speeds, and the complex flow interactions occurring between closely-arranged wind turbines and farms [2][3][4]. To investigate these topics, the U.S. Department of Energy has funded the American WAKE experimeNt (AWAKEN) [5], which focuses on wind farms located in the Southern Great Plains in Oklahoma.…”

Section: Introductionmentioning

confidence: 99%

“…Among them, scanning pulsed Doppler wind light detection and ranging (LiDAR) represents a primary asset for the present study given its long scanning range (> 2000 m), its high temporal (≈ 1 s) and spatial resolution (≈ 20 m), and its flexible scanning strategies. Doppler wind LiDARs have been successfully used to quantify both atmospheric-boundary-layer (ABL)-related events, such as low-level jets (LLJs) [7,8], and wind farm-related phenomena, such as global blockage [9] and wake losses [3,10]. Furthermore, the long range scanned by pulsed Doppler wind LiDARs makes this instrument compelling for investigation of farm-to-farm interactions, whose impact on annual energy production (AEP) still has not been fully quantified [11].…”

Section: Introductionmentioning

confidence: 99%

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LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment

Puccioni

Iungo

Moss

et al. 2023

J. Phys.: Conf. Ser.

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The exponential growth of wind energy and the need to exploit wind resources over areas with higher energy potential have led to the construction of neighboring wind turbines and farms with relatively small separation distances. As a result, for specific wind and atmospheric conditions, the wakes generated by an upstream wind farm may affect wind resources available for a downstream wind farm resulting in detrimental impacts on energy harvesting and structural loads for the downwind wind turbines. Distances between neighboring wind farms are typically larger than those associated with intra-wind-farm wake interactions, generating cumulative wakes whose characteristics might differ from those predicted through classical engineering wake models. These phenomena are referred to as farm-to-farm interactions. A better understanding and characterization of farm-to-farm interactions is one of the science goals tackled by the ongoing American WAKE experimeNt (AWAKEN). The site under investigation for this field campaign comprises two large wind farms in northern Oklahoma, USA, which are spaced roughly 5km apart along the prevailing South-North wind direction. To investigate possible interactions between these two wind farms, the WindFluX mobile LiDAR station has been deployed mainly to perform volumetric scans over their gap region. In this paper, preliminary results from these LiDAR volumetric scans will be discussed, specifically for a case with multiple wind turbine wakes evolving during the occurrence of a low-level jet.

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Section: Overview Of the Experimental Data Setmentioning

confidence: 68%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment

Puccioni

Iungo

Moss

et al. 2023

J. Phys.: Conf. Ser.

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“…For example a 10-20%, reduction of average power production was attributed to the wake effect for an offshore wind farm [1]. The losses for turbines at the second row of an onshore wind farm in unstable atmospheric conditions were estimated to be 20-40%, and 40-60% under stable conditions [2]. Better understanding and modelling of the wake effect could contribute towards reducing losses of such significance.…”

Section: Introductionmentioning

confidence: 99%

“…The impact of turbine clustering on power production has been observed using wind turbine operational data [1,2]. Such results are challenging to reproduce due to the large range of scales present in wind farm flows.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Mode Decomposition of merging wind turbine wakes

Zormpa,

Le Clainche,

Ferrer

et al. 2023

J. Phys.: Conf. Ser.

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The design and operation of wind farms is significantly affected by the impact that upstream turbine wakes have on the power production and fatigue loading of subsequent turbines; often called the wake effect. In this work, two types of flows are considered: the wake of a single turbine with a laminar inflow and the combined wake of two turbines operating in-line where the upstream wake results in an unsteady inflow for the downstream turbine. Those two scenarios are simulated using large eddy simulation (LES) and the actuator line method (ALM). The spatio-temporal velocity fields are analyzed by means of high order dynamic mode decomposition (HODMD), a well established variant of the DMD. The results show that most of the higher frequencies characterizing the laminar case are instead dominated by the lower frequency modes in the combined wake. This suggests that structures emerging from the blade rotations in a wind turbine wake may be less significant for describing the wake dynamics when the rotor is operating in the unsteady wake of an upstream rotor.

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Abstract: The cover image, by Said El‐Asha et al., is based on the Research Article Quantification of power losses due to wind turbine wake interactions through SCADA, meteorological and wind LiDAR data, DOI: .

Cited by 2 publications

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LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment

LiDAR Measurements to Investigate Farm-to-Farm Interactions at the AWAKEN Experiment

Dynamic Mode Decomposition of merging wind turbine wakes

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