WindFarmer models are continually validated and to inform updates to the Wake, Blockage, Energy and other models. The papers, presentations, webinars and reports below are a useful selection from historical validations of the models within WindFarmer.
Title | Date | Event / type | Models | Notes |
---|---|---|---|---|
Boundary layer educated long range wake estimates from WindFarmer CFD.ML | Jun-24 | WindEurope Technical Workshop, Dublin - Presentation | Wakes; CFD.ML | The inclusion of atmospheric conditions in the CFD.ML model training has improved our capability to capture the long-range wakes. |
CFD.ML – A new hope for rapid turbine interaction modelling? | Oct-23 | ACP Resource and Technology, Austin, Texas - Poster | Wakes; Blockage; CFD.ML | Poster introducing the CFD.ML turbine interaction model and latest validation. |
Big cluster & far-field wakes - an assessment of multi-fidelity models against North Sea wind farms' SCADA data | Oct-23 | ACP Resource and Technology, Austin, Texas - Poster | Wakes; RANS CFD | The 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. |
AI for turbine interactions: testing the intelligence of CFD.ML | Jun-23 | WindEurope Technology Workshop, Lyon - Presentation | Wakes; Blockage; CFD.ML | An introduction to DNV's CFD.ML turbine interaction model. Validation of it's skill in predicting blockage, internal wakes and external wakes offshore. Patterns of front row production show the model captures blockage impacts well. |
Blockage and cluster-to-cluster interactions from dual scanning lidar measurements | May-23 | WESC, Glasgow | RANS CFD, Wakes, Blockage | Collaboration between ENBW and DNV testing RANS CFD against direct measurements of cluster wakes and blockage from LIDAR wind speeds and also SCADA power measurements. |
Creating the next generation of validated turbine interaction models for offshore wind farms (Webinar) | Jun-20 | Webinar | Wakes; CFD.ML | Webinar describing the 2022 DNV validation of internal and external wakes for multiple DNV models. A justification for updated DNV Large Wind Farm Correction (LWF) settings used offshore to capture external wakes is shared. We present the internal wake effect validation described in the paper: T Levick et al 2022 J. Phys.: Conf. Ser. 2257 012010 |
Validating the next generation of turbine interaction models (paper) | Mar-22 | WindEurope Annual Event Bilbao - Paper | Wakes; CFD.ML | T 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 |
Improving confidence in wake predictions through operational validations | Jun-17 | WindEurope Offshore - presentation | Wakes | Patterns of production at onshore and offshore large wind farms presented and compared to WindFarmer Eddy Viscosity + LWF model. Investigation into LWF settings for onshore projects in different stability conditions support our +0.03 or +0.05 increased roughness adders. |
Impact of Large Neighbouring Wind Farms on Energy Yield of Offshore Wind Farms | Nov-11 | EWEA Offshore Conference, Amsterdam - Paper | Wakes | The WindFarmer large wind farm correction methodology is explained, including the recovery profile, with validation against offshore wind farms. |
New Developments in Wake Models for Large Wind Farms | May-09 | Paper | Wakes | Onshore large wind farm model and validation. The original evidence supporting the application of the WindFarmer LWF model onshore, including our application of the increased roughness = Base roughness + 0.03 input for onshore sites. |
Measuring and Modelling Wind Farm Blockage Offshore | Sep-21 | WindEurope Technology Workshop - Presentation | Blockage | Validation using upstream long-range lidar to test the wind speed profiles in collaboration with the European offshore developer EnBW. Results shows DNV's RANS CFD model replicates the wind profiles well when WRF is used to define for boundary conditions, supporting the magnitude of the DNV blockage correction. |
Wind-Farm-Scale blockage | Feb-20 | WinterWind - presenation | Blockage, RANS CFD | Testing DNV's BEET blockage correction against RANS CFD at onshore wind farms. Comparisons of CFD to front row of wind farm profiles show that CFD captures blockage well. BEET predictions are compared to CFD for 12 onshore wind farms that were not included in the BEET training set. Explanation of important drivers for blockage: layout and wind rose are less important. |
Blockage effects in WindFarmer: Analyst | Feb-19 | Webinar | Blockage | Rational behind the blockage effect and DNV's blockage correction models: BEET and RANS CFD. BEET is a surrogate for predictions of wind farm blockage predicted by DNV's high fidelity RANS CFD model. Discussion of the validation of BEET and how BEET may be used in WindFarmer. |
Wind Farm Blockage and the Consequences of Neglecting Its Impact on Energy Production | Jun-18 | Paper | Blockage; RANS CFD | J 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. |
WindFarmer white paper | Apr-16 | Report | Wakes, Blockage, Annual energy production | The basis for each WindFarmer energy and wake model component, demonstrated using comparisons to project data and case studies. Learn how WindFarmer's most advanced models (in 2016) provide you with the most accurate energy predictions. |
WindFarmer Validation Report | Apr-14 | Report | Shadow Flicker, Wakes, Blockage, Annual energy production | A overview of the WindFarmer models and summaries of the validation efforts (circa 2014). The validation report includes a Shadow Flicker validation not included elsewhere: See page 17 |