Publishers version - DTU Orbit

Figure 150: The accuracy (top plot) of evolved preview measurements w/o lidar distortion
(blue/dots) and with lidar distortion (green/diamonds); RMS blade-loads (lower plot) w/o
lidar distortion (blue/dots) and with lidar distortion (green/diamonds).
results are provided in Fig. 150. Simply introducing a set of wind speeds in the annulus that
are properly correlated with the existing TurbSim field without evolution results in a base
level of error relative to the wind speeds actually encountered by the blades; this is depicted
by the red-dashed line in the top plot of Fig. 150.
10.7.3 Simulation Results
Given the 0.7 m/s RMS base level of measurement error, the maximum benefit potential of
preview actuation is about a 10% drop in RMS blade flap relative to feedback-only control
as shown in the lower plot of Fig. 150. As expected, the benefit of preview in terms of RMS
blade loading reaches a maximum with 0.2 s (4 samples) of preview time. Without evolution
orlidareffects, previewgreaterthan0.2sdoesnotreallyimproveperformance. Withevolution
and no lidar distortion, blade load mitigation performance deteriorates with preview distances
greater than 0.2 s as measurement errors increase with distance from the rotor due to the
applied evolution. Because of the frequency dependent nature of the evolution model, these
measurementerrorstendtobemoresignificantathigherfrequenciesleadingtoover-actuation
by the feedforward control. By 10 s (180 m) of preview, the advantage of preview control
relative to feedback-only has been completely lost.
When applying preview based on a lidar measurement, large cone angles relative to the x
(downstream) direction result in significant contributions of the transverse v and vertical w
wind components to the estimate û of the downstream speed. This is apparent in the sharp
upward trend of the green-diamond curve as preview times are reduced below 3 s (< 54 m
preview, or equivalently a cone angle > 15 ◦ ); at these shorter preview distances the geometry
errors dominatethe preview measurement errors. At largerpreview times, evolutiondominates
thelidarmeasurementerror, butthesystemisbenefitingfromthelidarrangeweighting,which
low-pass filters the poorly correlated high frequencies in the wind. What is surprising is the
magnitude of the effect this filtering has on the quality of the load mitigation. Since the
214 DTU Wind Energy-E-Report-0029(EN)