We present a systematic framework for the validation and uncertainty quantification of wind farm wake models. The methodology is based on a new definition of the freestream wind speed. We apply the framework on data from 19 offshore wind farms. Our results show that the new wake model TurbOPark is overall unbiased and that the wake model error at each specific site does not depend on the mean turbine spacing. The Park model underestimates the wake loss unless a slower wake expansion than typically used is assumed. In either case, the Park model tends to underestimate the wake loss more for increasing distances between the turbines. We estimate the wake model uncertainty as less than 10% of the wake loss for the considered models.
A new analytical wake model for wind farm design is presented. The new model, TurbOPark, is based on the Park model but features non-linear wake expansion and a Gaussian deficit profile. The modelled wake expansion depends on the intensity of the local turbulence, which is a combination of ambient atmospheric turbulence and wake-generated turbulence. Moving downstream from the rotor, the intensity of the wake-generated turbulence decreases, and the wake expansion slows down. This leads to more persistent wakes in wind farms and clusters of wind farms with large distances between turbines. In the present study, we focus on the London Array wind farm and show examples of how results from Park and TurbOPark compare to SCADA data. We look at the array efficiency of the wind farm, the production of individual turbines, and the impact of neighbouring wind farms. We find that predictions from TurbOPark generally are closer to observations than predictions from the Park model.
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