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A large-scale validation compared wind farm parameterizations (WFPs) of the Weather Research and Forecasting (WRF) model to multi-year SCADA (supervisory control and data acquisition) data from six offshore wind farms. Although initially seven WFPs were considered, after preliminary assessment only three distinct ones were retained: the original Fitch (Fitch-O), a physics-derived axial-induction modification of Fitch (Fitch-pAIM), and the explicit wake parameterization (EWP). The study, conducted at 2 and 0.67 km resolutions, revealed total energy yield differences of ±5 % compared to SCADA data, with finer resolutions having a lower yield due to enhanced internal wake effects. The remainder focused on addressing the main sources of error affecting the total energy yield. The modeled mean wind speed was likely too low, leading to an energy yield underestimation. Only Fitch-pAIM accurately modeled the power curve and therefore the gross yield, while Fitch-O and EWP underestimated power by neglecting local induction effects. Internal wake magnitudes were well captured by Fitch-O and Fitch-pAIM at fine resolution, while EWP consistently produced wakes that were too weak. All WFPs showed signatures of global blockage and a dependency of wake losses on the vertical structure of the boundary layer. Lastly, external wakes were well captured by all parameterizations. The results demonstrate that Fitch-pAIM outperforms other WFPs at resolutions smaller than the turbine spacing. Despite the limitations in accurately reproducing distinct wake features in aligned and staggered configurations, WFPs accurately capture the total wake loss, making their use suitable for annual energy production (AEP) calculations.
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Sengers et al. (2026) studied this question.
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