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in the measurements is completely absent in the simulation. As already discussed
this is due to mass imbalance.
Blade load results are also shown in Fig. 12 for the same wind turbine now oper-
ated in a fl at terrain site [33]. In this case the mean wind is 15.4 m/s. However, a 6.0 o
yaw misalignment is present which explains the pronounced 1p variation on both
diagrams. Again the agreement between predictions and measurements is good.
In this particular case, predictions are shown also from a free wake aerodynamic
code [34] also showing good correlation to measurements.
The spectral information is the input to fatigue analysis. Fatigue is related to the
frequency content of load amplitudes. The basis of fatigue analysis is to count how
many times a specifi c load change (or range) appears. To this end, the load ranges,
i.e. the difference between a local min and the next max, are sorted in bins and the
number of samples (or cycles) per bin is recorded. In this way the cumulative
fatigue spectrums are produced. In Fig. 13 such spectrums are shown for the loads
Figure 11: PSDs of loads for a 500 kW stall wind turbine operating in complex
terrain at 13 m/s mean wind speed [32].
Figure 12: Azimuthal variation and PSD of loads of 500 kW stall wind turbine
operated in yaw [33].
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