1. Modelling the impact of wakes on power output at Nysted and Horns Rev R.J. Barthelmie, Indiana University USA/Risoe DTU DK K. Hansen, DTU Denmark S.T. Frandsen, O. Rathmann, RISOE DTU Denmark G. Schepers ECN, Netherlands K. Rados, NTUA, Greece W. Schlez, A. Neubert, GH, Germany L.E. Jensen, DONG Energy, Denmark S. Neckelmann, Vattenfall, Denmark Funding: NSF CBET-0828655, EU UPWIND # SES6 019945 EU POWWOW #SES6 019898 Data: DONG Energy A/S & Vattenfall AB (Horns Rev), Vattenfall and E. On Sweden (Nysted)

2. Modelling wakes in the UpWind project Problems 1.Preliminary analysis of wake power losses in large offshore wind farms larger than expected. Amended but high uncertainty 2.First v. large wind farms on land 3.Resources and wakes difficult to model in complex terrain 4.Multiple wind farms developed in same area Solutions 1.New parameters and/or next generation of wake models able to account for ‘deep array’ effect 2.(Assess the magnitude of the issue onshore) 3.Develop, apply and evaluate CFD 4.Assess, develop and evaluate models for whole wind farm modelling

3. Data In agreement with data owners some wind farm data have been made available Access is open and free (registration necessary) Offshore wake data from Vindeby Middelgrunden Horns Rev Nysted (in proc) Data processed into case studies for Horns Rev, Nysted (performance remains confidential) Access /registration details: http://mypage.iu.edu/~rbarthel/wakeslab.html

4. Wake models used in this project NameCompanyTypeCommercial/ Research WAsPRisø DTUEngineeringC WindfarmerGHAinslieC Risø FlowRisø DTUUnder development R WakefarmECNParabolised CFDC/R CENER FluentCENERCFDR NS FLowCRESCFDR NTUA CFDR

5. Offshore wind farms Wind farmNystedHorns Rev Owner DONG Energy (80%) E.On Sweden (20%) DONG Energy (40%) Vattenfall (60%) Turbine number7280 TurbineSiemens 2.3 MWVestas 2 MW Turbine typeActive stall, 2-speedPitch, variable speed Rotor diam (D)82.4 m80 m Hub-height69 m70 m Array8 (E-W) x 9 (N-S)10 (E-W) x 8 (N-S) Dist. between turbines 10.3 D (E-W) & 5.8 D (N-S) 7 D (E-W & N-S) Rated capacity165.6 MW160 MW Annual prod.595 GWh600 GWh Year comm.20032002 Water depth6-10 m6-14 m Distance land10 km (closest)14-20 km http://earthobservatory.nasa.gov/IOTD/view.php?id=3389 7.58.08.59.09.510.010.511.011.512.012.513.0 Longitude (° E) 54.5 55.0 55.5 56.0 56.5 57.0 57.5 L a t i t u d e ( ° N ) Horns Rev Nysted

6. Horns Rev and Nysted layouts Horns Rev 7D x 7D Nysted 10.5D x 5.8D

7. Data comparison Data from 2004-2006 Nysted, 2005 Horns Rev Selection on: wind speed ±0.5 ms -1 direction ±2.5º all turbines working in row all turbines working in neighbouring rows two subsequent observations for stationarity Gives relatively few observations in each category Data differences mainly due to spacing?

8. Model comparison at Horns Rev and Nysted

9. Exact row, narrow directions Seems to be a special case Agreement on wake behaviour at Horns Rev and Nysted Model agreement within ±10% Cross row angles Asymmetry in obs. and models Larger uncertainty ER ER+10º

10. Model comparison at Horns Rev and Nysted Consistency improved in model results High degree of uncertainty Differences between models Data issues Lower wind speeds Ongoing issues Asymmetry around central row Developing quantitative methods of evaluation e.g. efficiency Stability

11. Stability at Nysted Results from Barthelmie et al. European Offshore Wind 2007

12. Summary and future work Objective Reducing uncertainty in predicting power losses from wakes UpWind project Provides platform for undertaking model evaluation & data sharing Progress made Data analysis and modelling Wakes can be modelled with appropriate parameters Future Physical understanding of wake processes within and downwind wind farms

13. Other UpWind wake presentations and posters WIND TURBINE WAKE VIRTUAL LABORATORY: PROPOSAL FOR A NEW COLLABORATION PO.155 Rebecca Barthelmie, Indiana University, United States & Risø DTU, Denmark APPLYING FLOW MODELS OF DIFFERENT COMPLEXITY FOR ESTIMATION OF WIND TURBINE WAKES PO.156 Søren Ott, Risø DTU, Denmark A FAST PARAMETERIZED WAKE-MODEL FOR LARGE WIND FARMS PO.161 Ole Steen Rathmann, Risø DTU, Denmark CFD MODELING ISSUES OF WIND TURBINE WAKES UNDER STABLE ATMOSPHERIC CONDITIONS PO.163 Evangelos Politis, Centre for Renewable Energy Sources (CRES), Greece NEW DEVELOPMENTS IN LARGE WIND FARM MODELLING PO.167 Wolfgang Schlez, Garrad Hassan Deutschland GmbH, Germany CFD MODELLING OF THE INTERACTION BETWEEN THE SURFACE BOUNDARY LAYER AND ROTOR WAKE Daniel Cabezón, CENER, Spain