Environmental Engineering Reference
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than an hour after the run had completed. HIRLAM produced forecasts of hourly
wind speed and direction at a selected number of vertical levels for each wind farm
for look-ahead times out to 48 hours. These forecasts were spatially interpolated
from the four nearest HIRLAM grid points to the wind farm locations.
No online power measurements were available at the time of the trial. The
HIRLAM forecasts were thus the only online inputs to Prediktor. Considering
Figure 6.14 again, Prediktor firstly transforms the HIRLAM winds to the surface
using the geostrophic drag law and the logarithmic profile. The horizontal resolu-
tion of HIRLAM is such that it cannot model local effects at the wind farm. Pre-
diktor represents these local effects using correction factors calculated using Wind
Atlas Analysis and Applications Program (WAsP) which was also developed at
Risø National Laboratory and is the basis of the wind resource assessment techni-
que of the European Wind Atlas (Troen and Petersen, 1989). The local effects
modelled in WAsP are: shelter from obstacles, the effects of roughness and
roughness change and the speed-up/slow-down effects due to the height contours of
the surrounding terrain. Prediktor also takes account of wind farm array effects and
converts from wind speed to wind power output using correction factors calculated
using the PARK model which is an integral part of WAsP.
Prediktor also uses a model output statistics (MOS) module to take into account
any effects not modelled by the physical models. The MOS correction factors are
calculated offline from a comparison of predicted and observed power data.
The 15 wind farm locations are shown in Figure 6.15 and have a total capacity
of 106.45 MW, representing most of the installed wind power capacity in the
nw (56.66 MW)
w (20.09 MW)
sw (29.7 MW)
all (10 6 . 4 5 MW)
Figure 6.15
Location of wind farms (marked with triangles) and the division into
regional groupings (nw, w and sw)
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