CFD model validation

CFD model validation

DNV's CFD model has more validation than any other high fidelity RANS CFD flow model for wind farm flows. Also see WindFarmer model validation for related validation studies about turbine interaction modelling.

TitleDateEvent / typeModelsNotes
What really happens to wakes at high wind speeds?2026WindEurope annual event - MadridWakes: CFD, WRF-WFP, LongSim, EV-LWFWakes at high wind speeds are not as small as commonly assumed. Whilst the absolute turbine interaction losses are largest on the plateau of the thrust curve, the largest share of energy production occurs above 10 m/s, with substantial wake-loss magnitudes (>20% of energy loss).
ACP Mind The Gap2025ACP PEAKWakes + Blockage; CFD.MLAs below, presented to the USA audience
Mind the gap: mitigating the risk of AEP overprediction for the mega projects of tomorrow.2025WindEurope Technical Workshop, IstanbulWakes + Blockage; CFD.MLWindFarmer engineering models are benchmarked against DNV'S High fidelity CFD model predictions. We show a gap (an underestimate of losses compared to CFD) for current engineering models and a large error spread for tomorrow’s larger wind farms/clusters. However, our CFD.ML v2.6 model performed best, across a range of offshore wind farm scales, in a test where each prediction was made blind, not trained on data from that wind farm cluster.
Numerical Site Calibration: A validation study2025WhitepaperPower performance measurement
Cluster wakes and their effect on a wind farm annual energy production2024WhitepaperWakes; RANS CFD
Waking up to the magnitude of cluster and far-field wakes2024Wind Europe Technology WorkshopDNV CFD, RWE CFD, RWE VV, WindFarmer EV+LWFRWE-DNV collaboration looking effect on wind farm annual energy production from far-field wakes. Wind farm wakes detected in SCADA for distance of 30 km (250 RD) in both unstable and stable atmospheric conditions.
Several models are compared to measured SCADA production at two wind farms, Amrumbank and Triton Knoll.
Conclusions:
* Cluster wake impact on energy yield is large on plateau of thrust curve.
* Aggregated cluster effect (using synthetic FD):
* 3% - 4% for Amrumbank, and
* 2% to 4% for Triton Knoll.
* Differences between model predicted aggregated losses are within the typical uncertainties used for turbine interaction losses, though there is a tendency for the models best agreeing with the SCADA data (CFD models) to predict larger losses than the engineering models.
Validation of CFD-based flow curvature correction for LiDAR2024JWEA 46th Wind Energy SymposiumDNV CFD, LIDAR FCC
Beyond the Mast: Advancing Wind Measurements with CFD-Enhanced Lidar in Challenging Terrain2024ACP PEAKDNV CFD, LIDAR FCC
Modelling the convective boundary layer at microscale using RANS2023WESCDNV CFD
Blockage and cluster-to-cluster interactions from dual scanning lidar measurements2023WESCDNV CFD, Blockage correction, cluster wakesENBW - DNV collaboration measuring blockage and cluster wake impacts
Long distance offshore wakes2023Brazil Wind Power 2023DNV CFD, Long distance offshore wakes
Big cluster & far-field wakes, an assessment of multi-fidelity models against North Sea wind farms SCADA data2023ACP Resource and Technology, Austin, TexasWakes; DNV CFDThe effect of cluster wakes is investigated for the object wind farms of Amrumbank West (ARB) and Triton Knoll (TK), operating in different parts of the North Sea. Joint RWE and DNV work. Investigation of DNV and RWE RANS CFD, WindFarmer Eddy Viscosity and RWE Viscous Vortex model performance.
Blockage effects in a single row of wind turbines2022Journal of PhysicsDNV CFD; Blockage correctionCitation J Bleeg and C Montavon 2022 J. Phys.: Conf. Ser. 2265 022001. DOI 10.1088/1742-6596/2265/2/022001
Validating the next generation of turbine interaction models (paper)2022WindEurope Annual Event Bilbao - PaperWakes; CFD.MLT Levick et al 2022 J. Phys.: Conf. Ser. 2257 012010. A validation framework for testing of the internal wake effects is applied to 6 offshore projects to compare performance of 4 DNV wake models: WindFarmer Eddy Viscosity + Large Wind Farm Correction (LWF); Modified Park + LWF; CFD.ML; Stratified Eddy Viscosity
Measuring Wind Farm Blockage - First results from a 12-month scanning lidar campaign at a German offshore wind farm2021WESCDNV CFD; Blockage correctionENBW - DNV collaboration measuring blockage. For a shorter version of this deck see here
A Graph Neural Network Surrogate Model for the Prediction of Turbine Interaction Loss2020TorqueCFD.ML; DNV CFDTo cite this article: James Bleeg 2020 J. Phys.: Conf. Ser. 1618 062054
Wind Farm Blockage and the Consequences of Neglecting Its Impact on Energy Production2018PaperBlockage; RANS CFDJ Bleeg et al. Energies 2018, 11(6), 1609; https://doi.org/10.3390/en11061609 DNV's original paper with showing the magnitude of blockage effects, including validation of DNV's CFD model against measurements.
Wind Flow Assessments in Complex Terrain through CFD2017Mexico Wind PowerWind Flow; DNV CFD
Modelling stability at microscale within and above the ABL2015EWEAWind Flow; DNV CFD
An extensive validation of CFD flow modelling2015DEWEKWind Flow; DNV CFDSee here for the paper and also here for a slide deck
A systematic validation of CFD flow modelling for commercial wind farms sites2014EWEAWind Flow; DNV CFDSee here for the full paper and also here for a poster
CFD can consistently improve wind speed predictions and reduce uncertainty in complex terrain2012EWEAWind Flow; DNV CFDSee here for the full paper and also here for a poster
Investigating the treatment of forestry in CFD wind flow models2012CANWEAForested Wind Flow; DNV CFDAlso updated deck here
Modeling stable thermal stratification and its impact on wind flow over topography2012AWEAWind Flow; DNV CFD
Validation and challenges of CFD in complex terrain for real world wind farms2011EWECWind Flow; DNV CFD