How to Measure Public Wind?

Public Wind Measurements

Publicly available wind data can be useful if the wind monitoring stations are in locations that are representative of sites of interest for wind projects. An example would be a tall tower on a ridgeline that runs parallel to a similar ridge under consideration. Tall towers instrumented specifically for wind energy are strongly preferred. Airport and other weather stations can provide a rough indication of the wind resource, but often they are affected by poor data quality, and with their relatively low tower heights (10 m) is the international standard) they can easily be sheltered by obstacles such as buildings and trees. Such issues can sometimes be detected by plotting a time series of monthly or annual averages and looking for trends and discontinuities or long periods of missing data. In all cases it is important to obtain as much information as possible regarding each station to determine whether or not the data are reliable. Several elements should be considered in this determination:

  • Station location
  • Tower type and dimensions
  • Local topography, obstacles, and surface roughness
  • Sensor heights, boom orientations, and distances from tower
  • Sensor maintenance protocol and records
  • Duration of data record
  • QC and other adjustments applied to the data

Wind data tend to be more representative of the surrounding area where the terrain is relatively flat and uniform. In complex terrain or near coastlines, the ability to reliably extrapolate the information beyond a station’s immediate vicinity is more limited and may require expert judgment and wind flow modeling. Even in flat terrain, good exposure to the wind is essential, especially for short towers. Measurements taken in obstructed areas or on rooftops should not be used unless there is good reason to believe that the effects of the obstructions are small.

When comparing data from different stations, all wind speeds should be extrapolated to a common reference height (e.g. 50 m, a typical island wind turbine hub height). Wind speeds can be adjusted to another height using the power law equation:

Power law equation

v2 = the unknown speed at height h2
v1 = the known wind speed at the measurement height h1
α = the wind shear exponent. For most publicly available data sets, the wind shear exponent will not be known (and even if published, may not be reliable). Wind shear exponents vary widely depending on vegetation cover, terrain, and the general climate, and it is dangerous to offer estimates without detailed study. Nevertheless, some guidance may be helpful if treated with caution. Table 1 presents typical ranges of annual mean shear exponent based on our experience in different settings. (As a rule of thumb, an “inland” site is one that is at least 1-3 km from the shore in the prevailing upwind direction.)

Site ConditionsApprox. Range of Annual Mean Wind Shear Exponent
Shoreline, open0.08-0.15
Inland, open0.12-0.22
Inland, forested0.20-0.30
Table 1 Approximate wind shear exponent on islands

For example, suppose you have a set of measurements from a 10 m airport station at an inland site surrounded by many trees and other vegetation. The annual average wind speed from the station is reported to be 4.0 m/s. Assuming a mid-range shear exponent of 0.25 for this inland, forested site, you would project a mean speed at 50 m of 4.0 × (50/10)0.25 = 6.0 m/s. However, if the same station were on an exposed shoreline (assumed shear exponent of 0.12), the projected 50 m mean wind speed would be 4.0 × (50/10)0.12 = 4.9 m/s. A reasonable estimate of the uncertainty for these values is 1-2 m/s.

Ideally, data sets should span at least one year to reduce the effect of seasonal variations and should provide consistent data for at least 90 percent of that period. It is best to obtain and analyze the data in their original format, such as a time series of hourly or 10-minute wind speed and wind direction measurements. If only a summary is available, it should be used with caution unless the analyst is familiar with the QC procedures and analytical methods used and is confident they were correctly applied.

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