Implications of Small-Scale Flow Features to Modeling Dispersion over Complex Terrain

Banta, Robert M.; Olivier, Lisa D.; Gudiksen, P.H.; Länge, R.

doi:10.1175/1520-0450(1996)035<0330:iossff>2.0.co;2

Cited by 47 publications

(18 citation statements)

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“…The booms on this tower are directed to 278 • to capitalize on the most frequent direction for strong winds at the NWTC. These winds tend to be funneled from Eldorado Canyon, 5 km to the west of the NWTC (Banta et al 1996). Because the NWTC site experiences flow heterogeneity due to the complex terrain 5 km to the west of the site (Aitken et al 2014a, b), data from the M4 tower were also used, located 750 m south-south-west of the M5 tower.…”

Section: The National Wind Technology Centermentioning

confidence: 99%

Dissipation of Turbulence in the Wake of a Wind Turbine

Lundquist

Bariteau

2014

Boundary-Layer Meteorol

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The wake of a wind turbine is characterized by increased turbulence and decreased wind speed. Turbines are generally deployed in large groups in wind farms, and so the behaviour of an individual wake as it merges with other wakes and propagates downwind is critical in assessing wind-farm power production. This evolution depends on the rate of turbulence dissipation in the wind-turbine wake, which has not been previously quantified in field-scale measurements. In situ measurements of winds and turbulence dissipation from the wake region of a multi-MW turbine were collected using a tethered lifting system (TLS) carrying a payload of high-rate turbulence probes. Ambient flow measurements were provided from sonic anemometers on a meteorological tower located near the turbine. Good agreement between the tower measurements and the TLS measurements was established for a case without a wind-turbine wake. When an operating wind turbine is located between the tower and the TLS so that the wake propagates to the TLS, the TLS measures dissipation rates one to two orders of magnitude higher in the wake than outside of the wake. These data, collected between two and three rotor diameters D downwind of the turbine, document the significant enhancement of turbulent kinetic energy dissipation rate within the wind-turbine wake. These wake measurements suggest that it may be useful to pursue modelling approaches that account for enhanced dissipation. Comparisons of wake and non-wake dissipation rates to mean wind speed, wind-speed variance, and turbulence intensity are presented to facilitate the inclusion of these measurements in wake modelling schemes.

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Section: The National Wind Technology Centermentioning

confidence: 99%

Dissipation of Turbulence in the Wake of a Wind Turbine

Lundquist

Bariteau

2014

Boundary-Layer Meteorol

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“…During the winter, the downslope flow from the nearby Rocky Mountains is frequently channeled through Eldorado Canyon, located just west-northwest of the NWTC (Banta et al, 1996;Poulos et al, 2000Poulos et al, , 2007Clifton et al, 2013b;Aitken et al, 2014). The NWTC site slopes upward with about 20 m in elevation change toward the west for about 1.5 km before dropping off 20 m towards the highway on the western edge of the site.…”

Section: Measurement Sitementioning

confidence: 99%

Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

Martin¹,

Lundquist

Clifton

et al. 2016

Wind Energ. Sci.

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Abstract. Using detailed upwind and nacelle-based measurements from a General Electric (GE) 1.5sle model with a 77 m rotor diameter, we calculate power curves and annual energy production (AEP) and explore their sensitivity to different atmospheric parameters to provide guidelines for the use of stability and turbulence filters in segregating power curves. The wind measurements upwind of the turbine include anemometers mounted on a 135 m meteorological tower as well as profiles from a lidar. We calculate power curves for different regimes based on turbulence parameters such as turbulence intensity (TI) as well as atmospheric stability parameters such as the bulk Richardson number (R B ). We also calculate AEP with and without these atmospheric filters and highlight differences between the results of these calculations. The power curves for different TI regimes reveal that increased TI undermines power production at wind speeds near rated, but TI increases power production at lower wind speeds at this site, the US Department of Energy (DOE) National Wind Technology Center (NWTC). Similarly, power curves for different R B regimes reveal that periods of stable conditions produce more power at wind speeds near rated and periods of unstable conditions produce more power at lower wind speeds. AEP results suggest that calculations without filtering for these atmospheric regimes may overestimate the AEP. Because of statistically significant differences between power curves and AEP calculated with these turbulence and stability filters for this turbine at this site, we suggest implementing an additional step in analyzing power performance data to incorporate effects of atmospheric stability and turbulence across the rotor disk.

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“…Single DWLs have been extensively used in ABL studies for both flat and gently variable terrain, [13][14][15][16][17][18][19] over urban areas, [20][21][22][23] and for studies on wind turbine wakes at heights of hundreds of meters. 24 While the assumptions used for single DWL retrievals are appropriate for many situations, they are not suitable for highly complex and spatially variable turbulent flows in mountainous terrain.…”

Section: Introductionmentioning

confidence: 99%

Triple Doppler wind lidar observations during the mountain terrain atmospheric modeling and observations field campaign

Wang

Hocut

Hoch

et al. 2016

J. Appl. Remote Sens

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, "Triple Doppler wind lidar observations during the mountain terrain atmospheric modeling and observations field campaign," J. Appl. Remote Sens. 10(2), 026015 (2016), doi: 10.1117/1.JRS.10.026015. . The feasibility of observing large turbulent eddies was investigated by pointing three DWL at an intersecting probe volume adjoining a sonic anemometer mounted on the top of a meteorological tower. The time series and spectra of the sonic anemometer measurement were compared with the lidars. The lidar radial velocities closely followed those of the sonic anemometer, both in time and in the low frequency spectral domain, suggesting that the DWL technique is suitable for observing large turbulent eddies in the ABL. In addition, coordinated scanning triple DWL were used to directly measure the three-dimensional wind vectors, thus circumventing the assumptions required in using single or dual lidar deployments for full velocity measurements. The scanning triple lidar results were in satisfactory agreement with data from towerbased sonic anemometers. Notwithstanding, because of the difficulty of obtaining temporal and spatial synchronizations of the three lidars, the data were scant since a large amount of data had to be rejected in postprocessing. This difficulty is surmountable in the future by employing a robust control system for coordinated scanning.

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Implications of Small-Scale Flow Features to Modeling Dispersion over Complex Terrain

Cited by 47 publications

References 0 publications

Dissipation of Turbulence in the Wake of a Wind Turbine

Dissipation of Turbulence in the Wake of a Wind Turbine

Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

Triple Doppler wind lidar observations during the mountain terrain atmospheric modeling and observations field campaign

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