A case study of effects of atmospheric boundary layer turbulence, wind speed, and stability on wind farm induced temperature changes using observations from a field campaign

Xia, Geng; Zhou, Liming; Freedman, Jeffrey; Roy, Somnath Baidya; Harris, R. Alan; Cervarich, Matthew

doi:10.1007/s00382-015-2696-9

Cited by 50 publications

(47 citation statements)

References 24 publications

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“…For example, Roy (2011) andFitch et al (2013b) using a large-scale numerical weather prediction model [such as the popular Weather Research and Forecasting (WRF) model] found that large wind farms modify the near-surface air temperature and humidity as well as the surface sensible and latent heat fluxes, resulting in lower air temperatures during daytime and warmer air at night. Similar trends were found in the field for existing large wind farms (Zhou et al 2012;Xia et al 2015). While the reported values of these changes were small, these observations generated considerable interest since most terrestrial wind farms are installed over existing farmland and such perturbations have the potential to affect crop dynamics (Calaf et al 2014) and irrigation demand (Higgins et al 2015).…”

Section: Introductionsupporting

confidence: 53%

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

Sharma

Parlange

Calaf

2016

Boundary-Layer Meteorol

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The effect of extensive terrestrial wind farms on the spatio-temporal structure of the diurnally-evolving atmospheric boundary layer is explored. High-resolution largeeddy simulations of a realistic diurnal cycle with an embedded wind farm are performed. Simulations are forced by a constant geostrophic velocity with time-varying surface boundary conditions derived from a selected period of the CASES-99 field campaign. Through analysis of the bulk statistics of the flow as a function of height and time, it is shown that extensive wind farms shift the inertial oscillations and the associated nocturnal low-level jet vertically upwards by approximately 200 m; cause a three times stronger stratification between the surface and the rotor-disk region, and as a consequence, delay the formation and growth of the convective boundary layer (CBL) by approximately 2 h. These perturbations are shown to have a direct impact on the potential power output of an extensive wind farm with the displacement of the low-level jet causing lower power output during the night as compared to the day. The low-power regime at night is shown to persist for almost 2 h beyond the morning transition due to the reduced growth of the CBL. It is shown that the wind farm induces a deeper entrainment region with greater entrainment fluxes. Finally, it is found that the diurnally-averaged effective roughness length for wind farms is much lower than the reference value computed theoretically for neutral conditions.

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Section: Introductionsupporting

confidence: 53%

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

Sharma

Parlange

Calaf

2016

Boundary-Layer Meteorol

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“…As showed in Figure 2, pixels with at least one turbine are defined as WFM (in total: 528 pixels in red dots), and NNWF (in total: 448 pixels in green dots) are selected in an area around the WFM that is 3-4 pixels wide and 3-4 pixels away from the nearest WFM. It is noted that the defined NNWF are far enough from the WFM to eliminate downstream impacts [11,29,35]. The black triangles in Figure 2 indicate the pixels (in total: 249 pixels) where the center of Guazhou county is located.…”

Section: Data Processing and Methodsmentioning

confidence: 99%

“…Based on the radiosonde observations, recent study finds that the turbine-induced turbulence relative to the background TKE plays an essential role in determining those in the magnitude of LST changes over the wind farms [29]. The strong wind speeds (Figure 3b) and the frequently complex Given the small size of our study region as well as the approach involved here, the contributions from the incoming radiation and the land surface properties (topography, land-cover type et al) to the warming impacts are likely been minimized [16].…”

Section: Possible Impacts Of Temporal Changes In Land Cover On Lst Vamentioning

confidence: 99%

“…Based on the radiosonde observations, recent study finds that the turbine-induced turbulence relative to the background TKE plays an essential role in determining those in the magnitude of LST changes over the wind farms [29]. The strong wind speeds (Figure 3b) and the frequently complex synoptic-scale weather events [12] in spring are more likely to induce strong background TKE, which will mask the turbine-induced turbulence effect and consequently contribute to the noisy warming signals (0.12 • C/8 years) in this season.…”

Section: Possible Impacts Of Temporal Changes In Land Cover On Lst Vamentioning

confidence: 99%

“…The seasonal and diurnal variations of such impacts are examined over Texas and their results consistently showed a nighttime warming during all seasons [24]. The possible contributions to these warming signals are also discussed and examined, e.g., wind speed [24], atmospheric stability, land cover, surface albedo [16], topography [27], and turbulence kinetic energy (TKE) [29]. It is pointed out the seasonal variations of wind speed and the relative ratio of TKE induced by the wind turbines compared to the background TKE should play a key role in explaining the above LST changes detected in USA [16,29].…”

Section: Introductionmentioning

confidence: 99%

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A Case Study of Land-Surface-Temperature Impact from Large-Scale Deployment of Wind Farms in China from Guazhou

2016

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Abstract:The wind industry in China has experienced a rapid expansion of capacity after 2009, especially in northwestern China, where the China's first 10 GW-level wind power project is located. Based on the analysis from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data for period of 2005-2012, the potential LST impacts from the large-scale wind farms in northwestern China's Guazhou are investigated in this paper. It shows the noticeable nighttime warming trends on LST over the wind farm areas relative to the nearby non-wind-farm regions in Guazhou and that the nighttime LST warming is strongest in summer (0.51 • C/8 years), followed by autumn (0.48 • C/8 years) and weakest in winter (0.38 • C/8 years) with no warming trend observed in spring. Meanwhile, the quantitative comparison results firstly indicate that the nighttime LST warming from wind farm areas are less than those from the urban areas in this work.

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Toward understanding the physical link between turbines and microclimate impacts from in situ measurements in a large wind farm

et al. 2016

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Recent wind farm studies have revealed elevated nighttime surface temperatures but have not validated physical mechanisms that create the observed effects. We report measurements of concurrent differences in surface wind speed, temperature, fluxes, and turbulence upwind and downwind of two turbine lines at the windward edge of a utility‐scale wind farm. On the basis of these measurements, we offer a conceptual model based on physical mechanisms of how wind farms affect their own microclimate. Periods of documented curtailment and zero‐power production of the wind farm offer useful opportunities to rigorously evaluate the microclimate impact of both stationary and operating turbines. During an 80 min nighttime wind farm curtailment, we measured abrupt and large changes in turbulent fluxes of momentum and heat leeward of the turbines. At night, wind speed decreases in the near wake when turbines are off but abruptly increases when turbine operation is resumed. Our measurements are compared with Moderate Resolution Imaging Spectroradiometer Terra and Aqua satellite measurements reporting wind farms to have higher nighttime surface temperatures. We demonstrate that turbine wakes modify surface fluxes continuously through the night, with similar magnitudes during the Terra and Aqua transit periods. Cooling occurs in the near wake and warming in the far wake when turbines are on, but cooling is negligible when turbines are off. Wind speed and surface stratification have a regulating effect of enhancing or decreasing the impact on surface microclimate due to turbine wake effects.

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A case study of effects of atmospheric boundary layer turbulence, wind speed, and stability on wind farm induced temperature changes using observations from a field campaign

Cited by 50 publications

References 24 publications

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

Perturbations to the Spatial and Temporal Characteristics of the Diurnally-Varying Atmospheric Boundary Layer Due to an Extensive Wind Farm

A Case Study of Land-Surface-Temperature Impact from Large-Scale Deployment of Wind Farms in China from Guazhou

Toward understanding the physical link between turbines and microclimate impacts from in situ measurements in a large wind farm

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