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WIREs Energy Environ.
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Wind conditions and resource assessment

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Abstract The development of wind power as a competitive energy source requires resource assessment of increasing accuracy and detail (including not only the long‐term ‘raw’ wind resource, but also turbulence, shear, and extremes), and in areas of increasing complexity. This in turn requires the use of the most advanced large‐scale meteorological models and data together with a chain of modeling tools linking the large‐scale dynamics via the mesoscales to site‐specific wind conditions. These wind conditions (at a given wind turbine site and height) are a complex function of ‘the weather’ statistics and of influence from features at smaller scales such as hills and mountains, surface roughness conditions, surface thermal properties, and specific nearby obstacles such as ‘other’ wind turbines. This article is categorized under: Bioenergy > Science and Materials Energy and Development > Science and Materials
(a) Wake of the Rødsand 2 and Nysted wind farms for free wind speed U0 = 10 m/s and 270° wind direction. The colors show U/U0 at hub level. The dimension of the shown area is approximately 40 × 8 km. (b) Same as Figure a except that the normalized resource (U/U0)3 is shown. (c) Layout of the Rødsand2 and Nysted offshore wind farms.
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Idealized wind speed profiles in the (mid‐latitude) atmospheric boundary layer forced by a constant geostrophic wind of 12 m/s with homogeneous surface conditions (relatively smooth surface with a z0 of 2 cm) for various values of surface heating/cooling. Deep blue curve corresponds to relatively strong cooling (cloud free summer night), the gray curve to neutral (no heating or cooling), and the red curve to relatively important heating (daytime summer). The heat flux values are approximately (from blue to red): −12, −8, −4, 0, +40, +300 W/m2.
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Wind speed profiles showing the vertical near surface variation of wind speed over various homogeneous surfaces as indicated. It is assumed that the driving force (the large‐scale pressure gradient or geostrophic wind) is constant in the boundary layer (barotropic or nonbaroclinic conditions). All profiles approach the geostrophic speed of 12 m/s near the top of the boundary layer (of the order of 1000 m) in this example.
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Reanalysis data for a point in Ireland showing the variability of the mean wind speed. Red blocks show mean speeds over the calendar years, black blocks show 10 year means.
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A global map of the mean wind speed at 10 agl from 40 years reanalysis. A map corresponding to higher levels above ground (100 m agl say) would be very similar, but with a smaller land–sea contrast in general as the wind shear (vertical wind speed increase) over the sea is generally much smaller than over land (see Figure ). Because of the very coarse horizontal resolution of the reanalysis, the map is only indicative of the large‐scale wind systems, and not suited for any—even coarse—resource estimation.
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Wind measurements at low heights are strongly influenced by small‐scale features. The mean wind speed at 10 m above the terrain is indicated by the full line as function of the distance from the coastline at the left. Two measurement points are indicated by the anemometers and their mean speed values are indicated by the red circles. Straightforward interpolation would give the dashed line. Considerable error is introduced if the terrain effects are not adequately modeled. Similar errors may be introduced when vertical extrapolation of wind data are attempted without proper taking into account the local terrain characteristics.
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Mapping of wind resources using ‘top‐down’ and ‘bottom‐up’ approaches. Here, maps of mean speeds at 10 m agl over Europe is shown. Top left shows the mean values from the NCAR/NCEP reanalysis directly, same data as in global map (Figure ). Bottom left shows the map resulting from running a mesoscale model (WRF with a 45 km horizontal grid size) forced by the reanalysis data The right panel shows the resource map from the European Wind Atlas. The mean speed are given in m/s; color coding shown by the lower bar corresponds to the model data; for the wind atlas data, a range is given by the table (adapted from the European Wind Atlas).
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CFD flow simulation in complex terrain. The Ellipsys model is used to simulate flow in highly complex terrain around a reference site (red dot). The area shown is roughly 6 km by 6 km. Elevations range from 300 m (blue) to above 1000 m (red). Slopes are in excess of 50% at many places. The inflow is from the west (far outside shown area) and the black streak lines indicate flow speed and direction immediately above the surface. Discontinuities and ‘rotors’ of the streaklines indicate separation lines and areas of detached flow.
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Flow over an isolated hill (Askervein hill, see, Ref 18). The hill is elongated with a near Gaussian cross‐section as seen in the perspective plot of the hill. A transect extending 1000 m to both sides of the hilltop is indicated in blue. The hill is approximately 120 m high (the vertical scale is exaggerated by a factor 4). The colored curves above show the mean wind speed‐up factor relative to the upstream value for flow nearly along the transect from the left. The measured values at 10 m agl are shown by the green dots. Simulation with a linearized model (WAsP) is shown in blue, simulation with a RANS–CFD model (Ellipsys, Ref 19) is shown in red. The cyan and magenta curves correspond to the model simulations for the 50 m level agl.
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