Unformatted text preview: Wind and wake modelling
using CFD
Jens A. Melheim
CMR GexCon Wind Power R&D seminar, 2021 January 2011, Trondheim
Slide 1 / 21.01.2011, Wind Power R&D Seminar, Trondheim Outline
• Motivation
• CFD models
– Background
– Turbulence models
– Wind modelling • Wake models
– Wind deficit models
– Rotor models • Offshore wind farms
Slide 2 / 21.01.2011, Wind Power R&D Seminar, Trondheim Motivation
• Wake loss is a large uncertainty
when planning wind farms
• Computations of wake losses can be
used to:
1. Foresee energy output from a wind farm
2. Optimize wind farm layout • No industry standard for
computation of wake losses in
multiple wake cases Slide 3 / 21.01.2011, Wind Power R&D Seminar, Trondheim CFD  Computational Fluid Dynamics
• Solve the NavierStokes equations on a grid
• Impractical to resolve the smallest time and
length scales in a turbulent flow > solve
averaged or filtered NavierStokes equations
– Need model for unresolved scales –> turbulence model • Use a finite volume formulation
• Assume incompressible flow
– Predictioncorrection algorithm to obtain pressure field • Results can not be better than:
1. Models for unresolved physics
2. Boundary conditions Slide 4 / 21.01.2011, Wind Power R&D Seminar, Trondheim Turbulence models
• Closure for the unknown Reynolds stresses − ρ ui ' u j ' that
appear in the NavierStokes equations after
averaging/filtering
– RANS: Reynolds Averaged NavierStokes • Turbulent viscosity models
– Use a turbulent viscosity and mean velocity gradients to model
the Reynolds stresses
– Solve transport equations for 1 or 2 turbulence parameters
– kL, kε, kω • Reynolds stress models
– Solve transport equations for 6 Reynolds stresses + dissipation
rate of turbulent kinetic energy (ε) • Large eddy models
– Solve filtered NS eq. using a grid size dependent filter
Slide 5 / 21.01.2011, Wind Power R&D Seminar, Trondheim Characteristics of
wind farms
• Large domains (L=120 km)
• Large range of time and length
scales
• Moving rotors and high tip speeds
• Anisotropic turbulence in wake
regions
• Unsteady boundary conditions
Impossible to resolve all physics
Slide 6 / 21.01.2011, Wind Power R&D Seminar, Trondheim Implications
• Large domains (L=120 km)
– Only RANS based models applicable without using super
computers. • Large span of time and length scales
– Wall functions at ground / ocean
– Blades cannot be resolved in detail • Moving rotors with high tip speed
– Average over a rotor swept • Anisotropic turbulence in wake regions
– Turbulent viscosity models are not accurate in the near wake • Unsteady boundary conditions
– Assume steady state when planning Slide 7 / 21.01.2011, Wind Power R&D Seminar, Trondheim Wake models
• Explicit wake models
– Calculate wind speed deficit in the wake
– WaSP, WindSim • Parabolic models / Eddy viscosity models
– Start ~2D downstream of turbine using Gaussian wake profiles
– Solve simplified NavierStokes on axissymmetric grid or 3D grid
– ECN Wakefarmer, GH Windfarmer, FLaP (Uni Oldenburg) • Full CFD models
– Model turbine by momentum sink
– NTUA CFD, Ellipsys3D, CENER, CRES, RGU3DNS
Slide 8 / 21.01.2011, Wind Power R&D Seminar, Trondheim Wind turbine models
• Actuator Disc models
– Model rotor area by a porous disk
– Momentum sink uniformly distributed
– No mature model for turbulence generation • Actuator line / Actuator surface models
– Model each blade using a line or a surface
– Use BEM to calculate local forces
– Time step restricted by the tip speed • Direct methods
– Geometry models of moving blades (moving grid)
– Resolve flow at blade
Slide 9 / 21.01.2011, Wind Power R&D Seminar, Trondheim Wind
Profile
r d
r Summary of wake models
Model Pre Cons Multiple wakes? Explict models Quick
Very easy to use Need to tune parameters
No physics solved No Parabolic models/
Eddy viscosity Quick
Easy to use Terrain (2D models)
Multiple wakes Tuning needed Full CFD with
Actuator Disc
model Solve most physics
Easy input Slow
Turbulence production
Not accurate in near wake Yes Full CFD with
Actuator
Line/Surface Solve most physics
Accurate in near
wake Very slow
Requires detailed blade
and airfoil data Maybe Full CFD with
direct blade model Solve ”all” physics
Accurate in the near
wake Extremely slow
Much work to setup No Slide 10 / 21.01.2011, Wind Power R&D Seminar, Trondheim CFD – Actuator Disc
• Momentum sink in control volumes inside the
rotor area – uniformly distributed over disc area
• Turbulence production caused by wind turbine
– No established model for turbulence generation Slide 11 / 21.01.2011, Wind Power R&D Seminar, Trondheim Actuator Disc Improvement
• Blade Element Momentum (BEM) Theory yield a
better distribution of forces than the traditional
AD method.
AD: dFn = Ct 1
ρU 02dA
2 dFt = 0
BEM: = FL cos(φ ) + FD sin(φ )
dFn
= FL sin(φ ) − FD cos(φ )
dFt Slide 12 / 21.01.2011, Wind Power R&D Seminar, Trondheim Turbulence production
Pt 2
• El Kasmin & Masson (2008): Sε = Cε 4 ρ k
1
2
SU = − C x ( aU 0 )
• Rethoré et al (2009)
2
1
3
=
Sk
C x β p ( aU 0 ) − β d kaU 0
2
1 ε
3
=
Sε
C x Cε 4 β p ( aU 0 ) − Cε 5 β d kaU 0
2 k ( ) ( • BEM = α ( dFn − dFt ) aU 0
Sk
Sε = C1ε ε
k Sk A. El Kasmin & C. Masson (2008). Journal of Wind Engineering in
Industrial Aerodynamics 96:103122
P.E. Rethore et al. (2009). EWEC 2009
Slide 13 / 21.01.2011, Wind Power R&D Seminar, Trondheim ) Sexbierum experiment
• West coast of the Netherlands
• Polenko/Holec WPS 30 wind turbine
• Wind 10 m/s at hub height (35 m)
• Turbulence intensity 10%
• Thrust coefficient Ct=0.7
• Measurements 2.5D, 5.5D and 8D
downstream at hub height Slide 14 / 21.01.2011, Wind Power R&D Seminar, Trondheim Sexbierum experiment
• Wake wind speed deficit: x=2.5D x=5.5D Slide 15 / 21.01.2011, Wind Power R&D Seminar, Trondheim x=8D Conclusions
• The combination of full CFD with RANS based
turbulence model and Actuator Disc is a
promising technique for modelling of wake
losses in wind farms
• Better understanding and modelling of the
turbulence in the nearfield of the rotor are
needed
• Validation and benchmarking are key factors
for success Slide 16 / 21.01.2011, Wind Power R&D Seminar, Trondheim ...
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 Fluid Dynamics, power r&d seminar, Wind Power R&D

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