OFFSHORE WIND ACCELERATOR: WAKE MODELLING USING CFD

C. Montavon, ANSYS UKS.-Y. Hui, Dong EnergyJ. Graham, RWE Npower RenewablesD. Malins, Scottish Power RenewablesP. Housley, SSE RenewablesE. Dahl, StatoilP. de Villiers, The Carbon TrustB. Gribben, Frazer-Nash Consultancy

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Contents

Offshore Wind Accelerator Stage I

Wake modelling in ANSYS CFD

Results from blind simulations for Horns Rev and North Hoyle

Sensitivity – Turbulence model assumptions

Current understanding of limitations– Other turbine spacing/single wake analyses

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Offshore Wind Accelerator is a collaboration to reduce costs

60% (30GW) of licensed capacity in UK waters

Objective: Reduce cost of energy by 10% through collaborative RD&D

Initially 5 developers + Carbon Trust– 46% of licensed capacity in UK waters

(~22GW)– Launched Oct 2008, 1.5 year

commitment– Budget of £1.5m

Focusing on technologies for– Round 2 extensions– Round 3– Scottish Territorial Waters

This work was carried out under Stage I

Stage II is now underway– Three more developers– Commitment to 2014– Much larger budget

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OWA focuses on strengthening economics of offshore windStage 1 (Oct ’08 to Apr ’10) examined 4 research areas

Offshore wind returns

YieldOPEXCAPEX

Wake effects

AccessFoundation

sElectrical systems

Fin

an

cin

g c

osts

Four technology areas, selected on basis of detailed analysis of over 70 technical barriers

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Accuracy of models benchmarked vs actual data

“Case studies” formed basis of benchmarkingUnder-prediction of wake effects in many scenariosThe results enabled OWA to commission specific improvements to three packages and to develop one entirely new model– Sophistication of engineering and CFD models has been increased to add

greater realism and increase accuracy of predictions

ANSYS CFD

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Simple wake model in ANSYS CFD

Wind turbine orientation parallel to wind direction at inletUse mesh adaption during solution to resolve rotor diskWind turbine represented by momentum sink (constant thrust per volume at disk location)

Upstream wind speed in momentum sink obtained from actuator disk model and simulated wind speed at diskValidated for single wake cases (Vindeby, Nibe) and onshore (Blacklaw) 1

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2

1 UACThrustF DTi 2

2

1 UACThrustF DTi

1. C. Montavon, I. Jones, C. Staples, C. Strachan, I. Gutierrez, 2009, Practical issues in the use of CFD for modelling wind farms, http://www.ewec2009proceedings.info/allfiles2/70_EWEC2009presentation.pdf

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Horns Rev Wind farm characteristics

8x10 WTDiameter of 80mHub height of 70mWind turbine spacing: 7 diametersDomain size:

•10 km radius•1.0 km height

Thrust curve: Vestas V80ABL boundary layer profiles at inlet

(Richards and Hoxey)

20 km

20 km

geou

z

zln

uu ),

~(min0

*

z

u~

3*

0,max~ zzzz ground

22

3inletrefTIuk

22*

k

uC

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Results at hub height

Horizontal velocityHorizontal velocity Turbulence intensityTurbulence intensity

Uref = 10 m/s at 70m, z0 = 0.0001m, upstream TI = 6%Wind direction: sector 285

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Horns RevNormalised power down a row

Simulations by step of 1 degree, sector 270 – 285, averaged for three different bin sizes.Reasonably good prediction

– Tendency for over-estimation of array losses

– Good prediction of slope down the row

Consistent for various bin sizes

Upwind data from “Wake Measurements Used in the Model Evaluation”. K.S. Hansen, R. Barthelmie, D. Cabezon and E. Politis. Upwind Wp8: Flow; Deliverable D8.1 Data. 18 June 2008.

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North Hoyle

Same setup as Horns Rev, for different layout (6x5 array).Wind direction 260Reference wind speed of 10m/s at hub height (67m)Upstream TI of 7%Vestas V80Wind turbine spacing: – 4.4 D in 350 degree direction– 10 D in 260 degree direction

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North HoyleNormalised power down a row

Very good agreement with power data for both bin sizesAbsolutely blind test case!

Uref = 10 m/s at 67m, z0 = 0.0001m, upstream TI = 7%Wind direction: sector 260

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Typical convergence/resource requirements

Based on Horns Rev1.4 M Nodes in final mesh42 mins/run, start to finish, including I/O, partitioning and adaption16 cores, Intel Xeon (2 dual processor quad core systems, 16 MBytes/systemTypically 60 iterations on final adaption step for convergence, 110 in totalVery tight convergence criterion, rms residuals < 1E-6 (1E-5 would reduce iterations to 47)Total time less than 12 hrs start to finish for 15 simulations

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So far…

Good prediction of array efficiency rsp. normalised power down a row for Horns Rev (7D spacing) and North Hoyle (10D spacing)How robust are the results to changes in– mesh resolution– turbulence model setup– turbine spacing

Details in paper !

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Cases presented

K- turbulence modelUref = 10 m/s at 70mVariation on turbulence setup– Case A – Reference model, using high roughness value to

provide required turbulence intensity at inlet– Case B – Modified Cμ to provide required inlet TI while using a

roughness value more appropriate for sea– Case C – As Case B with modified turbulence decay rate 1

1. 1. Rados et al, CFD modelling issues of wind turbine wakes under stable atmospheric conditions, http://www.ewec2009proceedings.info/allfiles2/564_EWEC2009presentation.pdf

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Array efficiency: comparing cases A, B and C

Case A and C showing best agreement with production data1

Strong effect of change of turbulence model constants Are these changes in the model constants required because of incomplete representation of the physics of the atmosphere?– Stability conditions?– Large scale transient?– Interpretation of tke?– more validation required to

justify choice of constants

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

270 275 280 285 290

Eff

icie

nc

y

direction

Array efficiency

Case ACase BCase CBarthelmie et al, s270-285Barthelmie et al, s255-270

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

270 275 280 285 290

Eff

icie

nc

y

direction

Array efficiency

Case ACase BCase CBarthelmie et al, s270-285Barthelmie et al, s255-270

firstrow

windfarm

PN

P

1. Barthelmie et al , Modelling the impact of wakes on power output at Nysted and Horns Rev, http://www.ewec2009proceedings.info/allfiles2/301_EWEC2009presentation.pdf.

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Nibe - single wake

SSTSST

k-k-

Normalised wind speed at 2.5D, 4.0D, 7.5DNormalised wind speed at 2.5D, 4.0D, 7.5D

k- : good at distances > 6D, over optimistic at smaller distancesSST: excellent at distances ~3D, over pessimistic at larger distances

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Conclusions

Simple actuator disk model and associated framework based on ANSYS CFD– WindModeller

Provided good (or encouraging) results for array efficiency and power down row of turbine from blind tests of Horns Rev and North Hoyle. (spacing of 7D and 10 D)– Results sensitive to turbulence model assumptions

Affordable tool for detailed final wind farm layout analysisPotential for new insights into 3D effects afforded by this approach is clear