Using validated, high-fidelity long-range wake loss modeling, ArcVera Renewables found in their new study that commonly used engineering wake models vastly underpredict energy losses due to external wakes.
he study confirms the severe under-prediction of long-range wake losses by engineering wake loss models in common use and investigates long-range wake loss potential at the New York Bight offshore development sites.
Velocity deficits, as high as 1 m/s or 10%, persist up to or greater than 100 km downwind of large offshore arrays, leading to long-range energy deficits much greater than expected by most subject matter experts in the industry.
Improving wind asset risk and operational performance assessments
ArcVera used the Weather Research and Forecasting (WRF) model, while the Wind Farm Parameterization (WFP) was added to the model to account for the effects of the wind turbines in the domain. According to Greg Poulos, CEO of ArcVera Renewables:
WRF-WFP’s results here show that engineering wake or WFAI models currently under-predict long-range wake losses by a significant margin. Unexpected losses are likely to accrue from wind farms once thought to be too far away to be material to project performance
Further research is needed
As the study says, engineering models commonly used to estimate wakes have been validated for internal wakes and nearby external wakes but have not been validated regularly at such long distances and have not been validated at all for large nameplate (> 12 MW) and rotor diameter (> 200 m) wind turbines.
On the other hand, the WFP in WRF has been validated against SCADA recorded production for an onshore case by ArcVera, and it was accurate with respect to long-distance wakes within 16% at a 5-km (50 rotor diameter) range. This tool is actively used to reduce risk and optimize wind farm design.