windfarm flow modelling using cf d
TRANSCRIPT
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Wind Farm FlowModelling Using CFD
2012 Update Webinar
Christiane Montavon, Ian Jones
ANSYS
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15:00 Introduction to the webinar and ANSYS
15.10 Presentation
Why CFD Simulation?
Validation and technical advances
Overview of ANSYS CFD tools for wind farm flow modelling
15.45 Software Demonstration Automated workflow for wind farm modelling
16.05 Question and Answers
16.15 Close
Agenda
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Carbon Trust, project CT090-091, Power from OnshoreWind Farms, and partners,
RWE, Scottish Power, SgurrEnergy
Carbon Trust OWA Phase 1 and partners
(Dong, RWE, Scottish Power, SSE Renewables, Statoil,Frazer-Nash).
SSE Renewables
E.ON
EU BREIN project
Loughborough University
University of Strathclyde...
and many more
Acknowledgements
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Site selection, land and
sea
Generator and shaft design
Wind farm configuration for
optimal power generation
Blade design
Rotor sizing
and acoustics
Tower design
and FSI
Offshore Installation and
certification
ANSYS:A Comprehensive Simulation Platform
Electric Machine
Transformer
Power Distribution
Speed Sensor
Electromechanical
Component
Power Electronic
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More and more onshore sites developed in complex terrain and
complex forestry environment.
Associated risks:
Separation, negative shear exponent factors
Increased turbulence
implications for turbine longevity and energy output
On such sites, standard industry tools (linearised models) used outside
of the envelope where they are meant to operate
Large array losses, particularly so offshore
Empirical models tend to underestimate the losses for large arrays
Atmospheric stability significantly affects array efficiency (e.g. L. Jensen, EWEC
proceedings, Milan 2007)
CFD models increasingly advocated to address these issues.
Need for fidelity of solution and reliability validation!
Need for automated solution for users without CFD background
Background
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N-S Solvers vs. Linearised models
Advantages of Navier-Stokes solvers as
compared to linearized models:
Accurate prediction of turbulence:
- flow turbulence is modeled or resolved using RANS/LES
Better prediction of multiple-wake effects
- accurate geometry description and wake prediction from
multiple installations
- no limit to number of wind turbines considered
Separation/shade effects due to complex terrain- complex terrain is resolved
- shading effects, recirculation and separation are captured
Ref. 2
Ref. 1
Ref. 1
1. Barthelmie, R.J et al., Modelling and measurements of wakes in large wind farms, Journal of Physics: Conference Series 75 (2007) 012049.
2. Barthelmie, R.J et al., Modelling Uncertainties in power prediction offshore, IEA, Risoe, March 2004.
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On range of sites
Onshore: Blacklaw, An Suidhe, Nant y Moch, Harestanes
Offshore: Horns Rev, North Hoyle
On range of issues
Complex terrain
Complex forestry
Stability
Wake interaction
Some done by our users
Offshore: Burbo Bank, Gunfleet Sands, Barrow (DONG
energy)
Forestry: Loughborough University
Validation material
CFD delivers increased accuracy and insight in flow conditions
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ExampleBlacklaw Power Prediction
Complex forestry
Significant wake effects
Good prediction of normalised power
output
RMSE for power prediction over all
turbines and over both masts is 8.5%
R. Spence, C. Montavon, I. Jones, C. Staples, C. Strachan, D.
Malins, 2010, Wind modelling evaluation using an
operational wind farm site,
http://www.ewec2010proceedings.info/allfiles2/517_EWEC
2010presentation.pdf
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Forestry model (resistive model)
Variable forestry height
Variable loss coefficient
Wake Model, large array losses
Horns Rev, North Hoyle
Atmospheric stability accounted for via equation for
potential temperature, buoyancy effect in turbulence
model
Harestanes, An Suidhe
Horns Rev
Technical Advances
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Resistive Canopy Model
available:
Svensson
Lopes da Costa
Katul
Resistance in momentum only
Canopy Input Data
From roughness data
CFX Interpolation Table
variable tree heights
Forestry loss coefficient
Constant or variable with height
Forest Canopy Model
Max Forestry Loss Coef
Height Max
Galion Lidar data
CFD
Flow separation off forested region
C. Montavon, I. Jones, D. Malins, C. Strachan, R. Spence, R. Boddington, 2012, Modelling of wind speed and turbulence intensityfor a forested site in complex terrain, EWEA 2012, Copenhagen.
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Horns RevResults at Hub HeightSector 280
Horizontal velocity Turbulence intensity
Uref= 8 m/s at 70m, z0= 0.0002mWind direction: sector 280
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0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5 6 7 8 9 10NormalisedPower
Turbine Group
10m/s 270 2 bin
ANSYS CFD
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5 6 7 8 9 10
Normalis
edPower
Turbine Group
10m/s 270 10 bin
ANSYS CFD
Data - UpWind
0.4
0.6
0.8
1
1.2
1 2 3 4 5 6 7 8 9 10
Normalis
edPower
Turbine Group
10m/s 270 30 bin
ANSYS CFD
Data - UpWind
Horns Rev
Normalised Power Down a Row
Simulations by step of 1 degree, sector 270285, 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 WakeMeasurements 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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0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5
Norm
alisedPower
Column
10 deg bin
ANSYS CFD
Measured Data
Upper 25%
Lower 25%
0
0.2
0.4
0.6
0.8
1
1.2
1 2 3 4 5
Norm
alisedPower
Column
30 deg bin
ANSYS CFD
Measured Data
Upper 25%
Lower 25%
North Hoyle
Normalised Power Down a Row
Very good agreement with power data for both bin sizes
Absolutely blind test case!
Uref= 10 m/s at 67m, z0= 0.0001m, upstream TI = 7%Wind direction: sector 260
C. Montavon, S.-Y. Hui, J. Graham, D. Malins, P. Housley, E. Dahl, P. de Villiers, B. Gribben, 2011, Offshore Wind Accelerator:
wake modelling using CFD, EWEA 2011, Brussels.
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Improved results with atmospheric stability
Atmosphere on average stable
above boundary layer
Including this effect
Changes the relative distribution of
the wind speed between hill topsand valleys improves mast tomast cross prediction when masts
located in different type of
positions (i.e. hill tops vs valleys)
Improves the prediction of the
relative TI on site
Including surface stability effects
significantly affects the predictionof array losses
C. Montavon, C. Staples, C. Weaver, 2011, Simulating the flow conditions over complex terrain with RANS models: sensitivity to
a selection of parameters including atmospheric stability , EWEA 2011, Brussels.
C. Montavon, I. Jones, D. Malins, C. Strachan, R. Spence, R. Boddington, 2012, Modelling of wind speed and turbulence intensity
for a forested site in complex terrain, EWEA 2012, Copenhagen.
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4 masts on site, 3 near hill tops, 1 in a location with difficult flowconditions (valley, proximity to forestry)
Cross prediction done for 3 masts with long concurrent time series
Harestanes, Masts on site
All masts with data at 70m, 60m,40m, 30m
Hill top masts:
Holehouse Hill
Hareshaw Rig
Valley mast:
Bran Rig
Hareshaw Rig
Holehouse Hill
Bran Rig
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Maximum relative errors in wind speed cross predictions for three model
configurations:
1.Purely neutral
2. Conventionally neutral i.e. stableconditions in free stream, with
potential temperature gradient of US standard atmosphere, and neutralconditions at ground (adiabatic).
HarestanesMast to Mast Cross Prediction (wind speed)
3 masts (70m only) 3 masts (all heights)
Model BRAN-HOL BRAN-HAR HOL-HAR BRAN-HOL BRAN-HAR HOL-HAR
neutral 11.8% 13.3% 1.8% 24.0% 24.0% 3.2%
stable 0.4% 4.1% 5.4% 2.9% 6.5% 6.2%
Improved results with atmospheric stability
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Ongoing validation exercise together with end users,see e.g. our joint EWEA publications at
Copenhagen 2012, available from:
https://docs.google.com/open?id=0B6Cp_fvx8o5Dei0tenVqelZZQzQ
Brussels 2011, available from:
https://docs.google.com/leaf?id=0B6Cp_fvx8o5DMjBkMzQxNWMtOTk
xYy00ZmFiLWFlNzMtZGFhM2U0NWQ1ODFh&hl=en_GB
Previous years, available from:
https://docs.google.com/leaf?id=0B6Cp_fvx8o5DZmEzYzYxMDAtZGYxZi00YmI0LWIwMjYtZWM3NmViYWM2NDI3&hl=en_GB
Validated Tools
https://docs.google.com/open?id=0B6Cp_fvx8o5Dei0tenVqelZZQzQhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DMjBkMzQxNWMtOTkxYy00ZmFiLWFlNzMtZGFhM2U0NWQ1ODFh&hl=en_GBhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DMjBkMzQxNWMtOTkxYy00ZmFiLWFlNzMtZGFhM2U0NWQ1ODFh&hl=en_GBhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DZmEzYzYxMDAtZGYxZi00YmI0LWIwMjYtZWM3NmViYWM2NDI3&hl=en_GBhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DZmEzYzYxMDAtZGYxZi00YmI0LWIwMjYtZWM3NmViYWM2NDI3&hl=en_GBhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DZmEzYzYxMDAtZGYxZi00YmI0LWIwMjYtZWM3NmViYWM2NDI3&hl=en_GBhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DZmEzYzYxMDAtZGYxZi00YmI0LWIwMjYtZWM3NmViYWM2NDI3&hl=en_GBhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DMjBkMzQxNWMtOTkxYy00ZmFiLWFlNzMtZGFhM2U0NWQ1ODFh&hl=en_GBhttps://docs.google.com/leaf?id=0B6Cp_fvx8o5DMjBkMzQxNWMtOTkxYy00ZmFiLWFlNzMtZGFhM2U0NWQ1ODFh&hl=en_GBhttps://docs.google.com/open?id=0B6Cp_fvx8o5Dei0tenVqelZZQzQhttps://docs.google.com/open?id=0B6Cp_fvx8o5Dei0tenVqelZZQzQ -
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Beaucage, P., Robinson, N., Brower, M., Alonge, C.,Overview of six commercial and research wake models
for large offshore wind farms, Proceedings EWEA 2012,
Copenhagen.
Garza, J., A. Blatt, R. Gandoin and S.-Y. Hui (2011)Evaluation of two novel wake models in offshore wind
farms . Proceedings from the EWEA Offshore
conference, 29 Nov. - 1 Dec 2011.
Desmond, C., Sayer, A., Watson, S., Hancock, P., Forest
Canopy Flows in Non-Neutral Stability , EWEA 2012,Copenhagen. (poster award).
Clive, P., Dinwoodie, I., Quail, F., Direct measurement
of wind turbine wakes using remote sensing,
Proceedings EWEA 2011, Brussels.
ANSYS CFD Featured In Independent Publications
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WindModeller: set of tools wrapped around
ANSYS standard CFD products:
Allow non-CFD experts to perform wind farm analyses inautomated way
Drive ANSYS CFX or FLUENT flow solver
Allow advanced user to encapsulate their own expertise
(access to customised setup and post-processing scripts which
can easily be altered by the user to further develop the tools )
WindModeller Tools for Automated Solution
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WindModeller: Simulation Process
Wind farm simulation process from user perspective Set up analysis on desktop computer (either via GUI or command line)
Submit job to:
Run possible large number of cases on the local machine or on a remote server
Postprocess results to automatically generate reports/summary data files
Possibility to perform additional post-processing on individual results files using CFDPost
Setup on desktop
Run on local or remote
computer Report as html file
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Current recognised terrain format SRTM, Shuttle Radar Topography
Mission, freely available, 90mresolution (finer resolution in the US)
NTF, National Transfer Format, contourdata (UK)
.map files (WAsP format) Generic point data file (.csv)
Terrain converted to tesselatedformat (STL)
Meshing with custom tools
Fixed mesh structure, hexahedral mesh(5 or 9 blocks), aimed at processautomation
Template mesh morphed onto STLterrain representation
Variable mesh topology forelongated/twin wind farms
Meshing Approach
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Varying Mesh Topologies
Compact wind farm
Elongated wind farm
Twin wind farms
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User can prescribe:
horizontal resolution in central
region
Rate of horizontally expansion
outside
first layer cell heights in vertical
Good control of mesh resolution in
lower heights (ensures appropriate
resolution is achieved in forested
regions)
Smooth vertical expansion above
Meshing Controls
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Mesh Adaption on Wind Turbine Rotor
Improve resolution by automatically refining mesh around the turbine
location, from the specification of the rotor location and actuator diskparameters only
Automatically enabled if wake model is used.
Initial mesh 1strefinement
2ndrefinement
Final mesh
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Outer surface divided into 24
regions
12 for inlet b.c. (Dirichlet on
velocity)
12 for outlet b.c. (entrainment
conditions with prescribed static
pressure)
Setup automated to run for e.g.
12 wind directions
Selection of surfaces defininginlet/outlet automated in script
running cases for various wind
directions
meshing done only once
Setup
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Flow Modelling in WindModeller
Atmosphere modelled as: incompressible fluid (Air at 15C)
assuming neutral stability
solving for steady state RANS
Turbulence modelled via two-equation model Shear Stress Transport (SST) turbulence model or k- .
Ground modelled as rough wall (spatially variable roughness)
Inlet boundary conditions Classical constant-shear ABL profiles (Durbin & Petterson Reif ):
Additional physics: Forest canopy model(resistive term in momentum equation + additional source
terms in turbulence model)
Multiple wake model(actuator disk model) Atmospheric stability as beta feature
2/1
2
*
C
uk u
uln
z
z
* ( )
0 z
u
3
*
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Simple Wake Model
Wind turbine represented by momentum sink
constant thrust per volume within
identified rotor disk.
Wind turbine orientation parallel towind direction at inlet
Works on any type of mesh, althoughit is expected that the best resultswill be obtained with resolution thatcaptures the wind turbine diskreasonably well
User input:
Coordinates of hub location
WT diameter
WT thrust and power curve
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGL andprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor
Exported data tables of similarquantities at wind turbine/mast
locations Export to Google Earth (.kml files)
Automated report in html format
Post-Processing in WindModeller
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGL andprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor
Exported data tables of similarquantities at wind turbine/mast
locations Export to Google Earth (.kml files)
Automated report in html format
Post-Processing in WindModeller
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGLandprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor,flow angles
Exported data tables of similar
quantities at wind turbine/mastlocations
Export to Google Earth (.kml files)
Automated report in html format
Post-Processing in WindModeller
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGL andprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor ,flow angles
Exported data tables of similar
quantities at wind turbine/mastlocations
Export to Google Earth (.kml files)
Automated report in html format
Post-Processing in WindModeller
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGL andprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor ,flow angles
Exported data tables of similar
quantities at wind turbine/mastlocations
Export to Google Earth (.kml files)
Automated report in html format
Post-Processing in WindModeller
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGL andprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor ,flow angles
Exported data tables of similar
quantities at wind turbine/mastlocations
Export to Google Earth (.kml files)
Automated report in html format
Post-Processing in WindModeller
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGL andprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor ,flow angles
Exported data tables of similar
quantities at wind turbine/mastlocations
Export to Google Earth (.kml files)
Automated report in html format,including the above
Post-Processing in WindModeller
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As part of the automatedapproach WindModeller cangenerate:
Plots of streamlines
Identification of recirculation zones
Plots at constant height AGL andprofiles at wind turbine/mastlocations for quantities such asnormalised velocity, turbulenceintensity, shear exponent factor ,flow angles
Exported data tables of similar
quantities at wind turbine/mastlocations
Export to Google Earth (.kml files)
Automated report in html format,including the above
Post-Processing in WindModeller
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Wind Data Transposition Module
Simulations establish climatological relationships between wind conditions at
mast (reference site) and WTG (predicted site).
Simulations are performed independently from the data collection at the mast.
Data collected at mast
Wind conditions
predicted at WTG
Wind data transposition module
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Energy Assessment/Cross Prediction
Wind data for input:
Time series or Frequency tables
Allows for multiple masts and with
/ without wake calculations
Can deal with heterogeneous wind
farm Masts data collected before or
after wind turbines installed
Possibility to do a post-
mortem on an existing wind
farm to understandperformance issues of single
WT if mast still measuring
when wind farm is operational
Note: masts must be within simulation domain
(no MCP)
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Output from Data Transposition
Tables of Capacity Factors (bydirections and overall) summarising
the average annual energy output at
each WT.
Wind speed distributions (WAsP .tab
files) at WT and masts.
Resource file (WAsP .rsf) at WT
locations.
Summary table with average wind
speed at masts from cross prediction.
Summary tables of mean andrepresentative turbulence intensity by
wind speed classes at masts and WTlocations. (when working from time
series, including the wind speed
standard deviation as input).
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Customised tools based on standard ANSYS CFDsoftware under continuous development
Driven by customer and project demands
Used on many cases
Made available to customer on service based
approach via two stage process:
1stphase: demonstration of capability on terrain chosenby customer
2ndphase: Technology Transfer. Tools made available tocustomer, also includes one-to-one training, support
and maintenance of the tools after delivery.
Develop features on request.
Availability of WindModeller Tools
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OWA Phase II: integration of atmospheric stability andassociated effects on large array losses
Carbon Trust POWFARMM project: complex terrain,forestry, wakes, comparison with masts and Galion
LIDAR dataVarious consultancy projects recently completed for
customers
Pollution transport
Integration of buildings
More complex stability conditions (e.g. strong inversions,coastal low level jets)
Diversification into modelling of marine arrays
(TideModeller)
Ongoing Projects
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CFD delivers increased accuracy for
Complex terrain/complex forestry cases
Estimation of large array losses
Atmospheric stability improves accuracy compared to
neutral cases, which tend to be used by other CFDpackages in the industry
ANSYS has a suite of tools (WindModeller) that helpsyou automate the simulation process, with state of the
art models for
Forestry Wakes
Atmospheric stability
Validation material available to attest this.
Summary
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Upcoming ANSYS Events
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Friday, 11th May 2012
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