cfd for wind turbine

1. Flow Analysis of wind turbine
Dr. Sachin L. Borse
Professor and Coordinator International Relations,
Imperial College of Engineering and Research,
Nagar Road, Pune, India
PIN 412207
(Formerly Hydraulic Design Engineer, Klein
Schanzline Becker Pumps, India)
(Formerly Associate Professor, Shaqra university,
Saudi Arabia)
By
@
RSCOE, Pune

2. About Wind turbine
Wind – Atmospheric air in motion
Turbine – machine which absorbs fluid power and
generates mechanical power.
Wind energy conversion based on
conservation of energy.
Wind energy is converted to
mechanical energy.
Wind turbines use airfoils to extract
the kinetic energy in the wind
blowing past the turbine

3. About Wind turbine
Mechanical power = Torque *angular velocity
Angular velocity is decided by speed of turbine=2πN/60
Torque =Force *Radius
Force = rate of change of momentum
We want to create force.
Change of momentum is created by change in
direction of fluid. Thus force is created by change of
direction of fluid. This change is effected by turbine
blade.

4. Wind Turbine

5. About Wind turbine
Typically the twist is around 10-20° from root to tip.
For shockless entry, wind should enter in blade at
relative velocity. This compel us to twist the blade.
Blade speed =2πrN/60, where r is local radius

6. About Wind turbine
The tip speed ratio is the ratio of the blade tip
speed over wind speed. It is a significant parameter
for wind turbine design. A higher tip speed ratio
generally indicates a higher efficiency but is also
related to higher noise levels .
Generally a low speed wind turbine chooses
value of tip speed ratio from 1 to 4 and a high speed
wind turbine chooses its value from 5 to 9. As a
preliminary design consideration, the best range of tip
speed ratios for a high speed turbine is around 7,
which gives maximum power coefficient.
Betz limit, Betz = Cp=16/27 ≈ 0.593.

7. CFD is the simulation of fluid flow and heat transfer
systems using modeling (mathematical physical
problem formulation) and numerical methods
(discretization methods, solvers, numerical
parameters, and grid generations, etc.)
About CFD

8. How CFD helps in design?
1)It helps to predict performance of hydraulic and
thermal design
2) Plenty alternate options can be tried, which
otherwise difficult in experimental work
3) CFD gives detail insight of flow which otherwise
is difficult
4) Can be used to validate experimental and
analytical results.
5) This helps to make design process more scientific.

9. CFD Analysis :- steps
0)Decide your goal:- accuracy, time,
1)Identification of domain(geometry):-
Determine the domain size and shape.
Decide on possibility of geometry simplifications to
save time eg. 2D, symmetry, periodicity
2)Identification of right approximation
Viscous/Inviscid,
Laminar/Turbulent,
Incompressible / compressible,
Single-phase/multi-phase)
3)Identification of right solution method
Finite Element / Difference/Volume,
Structured/Unstructured mesh, Order of accuracy

10. CFD Analysis :- steps
4)Pre-processing:- Generate computational grid,
assign boundary conditions, set initial conditions,
compile code, prepare input parameters
Meshing

11. 5)Solution:-Run the code, monitor the solution
6)Post-processing:-Collect and organize data, analyze
results
7)Verification:-Do the results make sense? Are the trends
right? Does it agree with previous calculations on similar
configurations?
8)Validation:- Does the result agree with theory/
experiment?
CFD Analysis :- steps
At every step, good understanding of theoretical fluid dynamics and
heat transfer is essential.

12. CFD-Aim of analysis
what we look from Engineering analysis:
 forces (pressure , viscous stress etc.) acting on
surfaces (Example:1) In an airplane, we are interested in the lift, drag,
power, pressure distribution etc

13. CFD-Aim of analysis
what we look from Engineering analysis:
2)forces and torque acting on impeller blade)
 velocity field (Example: 1)In a race car, we are
interested in the local flow streamlines, so that we can design for less
drag. 2)we look for flow separation in turbomachinery which can be
corrected in future design)

14. CFD-Aim of analysis
what we look from Engineering analysis:
 temperature distribution (Example: 1)Heat transfer in the
vicinity of a computer chip 2)hot spot in gas turbine blade)
Ultimate aim is to predict the behaviour of systems, to design more
efficient systems.

15. Unknowns: Density (ρ), Velocity (u,v,w), Pressure (p)
Dynamics of fluids is then given by
 Conservation of Mass (Continuity equation)
Summation of Rate of mass flow rate in
= summation of rate of mass flow rate out
 Conservation of Momentum (Navier-Stokes
equations) [Newton’s second law]
Mass*acceleration in i direction =sum of forces in i direction
 Conservation of Energy (Energy equation) [First law
of thermodynamics]
Heat added = change in internal energy + work done
CFD-equations to be solved

16. CFD-Turbulence modelling
In real life most of fluid flow problem fall under turbulent category.
Turbulent flow has fluctuations in field which small in magnitude but
large frequency. Solving turbulent Navier stokes takes huge
computation resource. Hence turbulence modeling is required.
Flow becomes turbulent with following condition,
Re>2300 for internal flow eg flow inside duct or pipe line
Re>1*105 for external flow eg flow over aeroplane
Ra>109 for natural convection heat transfer eg hot surface in stand
still air

17. CFD-Turbulence modelling
Reynolds Averaged Navier stokes equation(RANS or RAS):- solves
time averaged Navier stokes Equation. All length scale are modeled.
Most widely used for calculating industrial flows. Faster and requires
less computer resources.
Eg.
Spalart Allmaras model (one equation )
k-epsilon model (two equation)
K-omega(two equation)
RSM( Six equation )
Large Eddy Simulation(LES):- Large eddies are solved, small eddies
are modeled. More expensive than RANS. Less expensive than DNS
Direct Numerical Simulation(DNS):-Turbulent NS is directly solved
without modeling.

18. CFD-Turbulence modelling
Reynolds Averaged Navier stokes equation(RANS or RAS):-
RANS may use wall function (eg k-epsilon model) to avoid large
number of elements at wall and thus reduces computation effort. In
such case y+ of boundary element should be in 30 to 100. More
preferred for industrial application.
When not using wall function eg (k-omega model) near wall element
should have y+ <2. Thus requires more number of elements. More
computation effort needed.

19. CFD for wind Turbine
Flow is considered as incompressible as velocity is
ranging from 4 to 25m/s.
Criteria for compressible flow(M>0.3)
Here M=25/340=0.1
Hence incompressible.
While dealing with Atmospheric Boundary Layer(ABL)
Boussinesq approximation taken into account to
include buoyancy effects.
Generally used turbulence model
RANS,
Now a days people started using LES as more
accurate but requires more computational resources.

20. CFD for wind Turbine
Purpose of CFD analysis
1)To find power generated by wind turbine
2)To find flow behavior in wind turbine(flow
separation)
3)To find effect of location of wind turbines in wind
farm

21. CFD for wind Turbine
Atmospheric Boundary Layer(ABL)
Boussinesq approximation taken into account to
include buoyancy effects.
Stratification
The atmosphere consist of parcels of different
densities, the tendency is to go up the ones that have
lower density and go down those of higher density
and the fluid is said to be stratified.
heavy parcels below light parcels-> system is stable.
lightest parcels below the highest-> unstable system
if no density difference with height-> neutral system

22. CFD for wind Turbine
Stratification
Neutral flow can be approximated to windy
conditions with cloud cover, whereas stably stratified
flow occurs mostly at night and unstable at very hot
sunny days.

23. CFD for wind Turbine
Spatial resolution of ABL and turbine at same time is
not possible.
Often, actuator models are used to reduce grid
requirements and simplify the problem. The actuator
disk model (ADM) represents the wind turbines as
disks that impose body forces on the flow field
depending on the fluid velocities.
Many versions of ADM exists. Some models
taking only the axial direction of the imposed force
into account and others taking only the axial and
tangential forces into account.

24. CFD for wind Turbine
• The basic idea of the actuator disc principle in
connection with rotor aerodynamic calculations, is
to replace the real rotor with a permeable disc of
equivalent area where the forces from the blades
are distributed on the circular disc.
• The distributed forces on the actuator disc alters
the local velocities through the disc and in general
the entire flowfield around the rotor disc.

25. CFD for wind Turbine
streamlines for a constantly loaded rotor disc

26. CFD for wind Turbine
Actuator disc Model
The model makes the following assumptions:
1)the pressure far upstream and downstream of the
turbine is constant,
2)the flow is incompressible,
3)the rotor has an infinite number of blades,
4)the thrust is uniform over the entire rotor.
Conditions p1=p4 and velocity across disc u2=u3

27. CFD for wind Turbine
Actuator disc Model
The axial induction factor= a
. . . . . . . . y
p1=p4 and u2=u3

28. CFD for wind Turbine
Actuator disc Model
The above relations set the pressure drop in the
simulations as a function of turbine power;
however, this pressure drop is assumed uniform
across the entire disc.
. . . . . . . . . . .X

29. CFD for wind Turbine
Actuator disc Model
Wind turbine blades typically have nonuniform blade
shapes that are not well represented by this uniform
assumption.

30. CFD for wind Turbine
Blade Element Momentum theory(BEM)
blade element momentum (BEM) theory determines
momentum extraction as a function of blade radius.
BEM is a useful tool for determining the net
performance of a non-uniform blade, which often use
more than one airfoil along the span.
BEM discretizes the blade radially and
determines performance parameters at each discrete
section. The net parameters can be taken as a
weighted sum of each radial section.

31. CFD for wind Turbine
Blade Element Momentum theory(BEM)
If a power coefficient of 0.5 which is representative
of modern machines. The power at each radial
section is calculated from the blade geometry. This
radially dependent power value for spanwise blade
stations is used in Equation x to determine the radially
dependent power coefficient (Cp).
From Equation this equation, the axial induction
factor (a) is determined as a function of radius from
the power coefficient (Cp).
Finally, the pressure drop is calculated from Equation
y as a function of radius.

32. CFD for wind Turbine
CT is Thrust coefficient and CP power coefficient
axial interference factor/ axial induction factor
Input to CFD software OpenFoam Actuator Disc Model

33. CFD for wind Turbine
Boundary conditions:
Initial conditions is
obtained by conducting
ABL simulation
Inlet:- inlet boundary
condition derived from
ABL simulation.
Effect of distance between two turbines on local flow
power.
Turbine considered here is 100m diameter with hub
height 100m from ground.

34. CFD for wind Turbine
Boundary conditions:
Outlet:- inletOutlet
(normally outlet but
reverse flow allowed)
Ground:- no slip
Top:- symmetry
Sides:- slip

35. CFD for wind Turbine
LES Model RANS Model(K-epsilon)

36. CFD for wind Turbine
Contours flow-direction velocity (m/s) for LES

37. CFD for wind Turbine
Turbine Power Ratio for LES and RANS(Standard k-
epsilon)

38. References
1)Timothy Stovall and Gary Pawlas, 2010, “Wind Farm Wake Simulations
in OpenFOAM”, 48th AIAA Aerospace Sciences Meeting Including the
New Horizons Forum and Aerospace Exposition, Orlando, Florida
2) Xabier Pedruelo Tapia, 2009, “Modelling of wind flow over complex
terrain using OpenFoam”, Master’s Thesis in Energy Systems, University
of Gavle.
3) Dnyanesh A. Digraskar, 2010, “Simulations of Flow Over Wind
Turbines”, Master’s Thesis , University of Massachusetts – Amherst
4) Anne Mette, 2013“Wake Modelling using an actuator disk model in
openFOAM” Master’s Thesis , Norwegian University of Science and
Technology.
5) L.A. Martinez Tossas and S. Leonardi , 2013, “Wind Turbine Modeling
for Computational Fluid Dynamics”, NREL/SR-5000-55054 ,