energy yield assessment and site suitability using openfoam - crasto, castellani (sowe 2016)

Giorgio CRASTO, Francesco CASTELLANI

[email protected]

Fourth Symposium on OpenFOAM® in Wind Energy. TU Delft 2-4 May 2016

Energy Yield Assessment and Site Suitability using OpenFOAM

Calculation of AEP by means of CFD

In this study is presented a computation of Annual Energy Production (AEP or P50) for two selcted sites:

–Hundhammer: it’s a Norwegian small island with one single ridge NW-SE oriented. In Hundhammer 17 wind turbines are deployed. A terrain description is available in the evaluation version of WindSim. Production not available.

–Test case 2: is a N-S oriented ridge; forested areas are present nearby with high roughness, up to 1.4m of roughness length. Production available.

2/23

Current Workflow

3/23

Grid generator -> terrain fitted coordinates; similar to the Terrain Block Mesher developed at the Fraunhofer Institute

•Writing of the case folder •Meshlab for .asc to .stl conversion

RANS simulations for a prescribed number of wind directions and neutral stratification. •The standard k-epsilon turbulence modelling

•SIMPLE solver (uncompressible, steady state)

Post processing: wind data, park layout, power CT curves and wind speed (U0, U1, U2) plus TKE (k) at met masts and turbines are combined to obtain the AEP.

GNU Octave 4.0

2.3.1 / 3.0.1

Test case 1: Hundhammer

4/23

Digital terrain model - Elevation (m).

Satellite picture (Google Earth)


5/23

Structured mesh created with the blockMesh.

The lower boundary fits to the ground.

The height of the first cell is set to 1.08m

=10.8*max(z0(x,y))


6/23

While the roughness length z0 is also mapped.


7/23

All cases (wind directions) converge smoothly to the

default residuals.

Residuals:

P 1e-3;

U 1e-4;

"(k|epsilon)" 1e-4

Version 2.3.1

Post processing

8/23

U0, U1 and k are sampled at the anemometers and

hubs locations.

A wind rose is therefore estimated at each hub

location, accounting for wakes by means of the

Jensen/Park model, see Katic et al (1986).

The energy production can be computed starting from

a wind rose (occurances vs wind and directions bins)

or a time history (all time steps).

Katic I, Højstrup J, Jensen N O. A Simple model for Cluster

Efficiency. EWEC 1986 Proceedings. 7-9 October 1986, Rome (IT)

Post processing

9/23

Looking at the gross AEP first, the numbers are very

similar and the two CFD models acted in a similar

manner;

More differences are found in the productions with

wakes; even if in both cases the Jensen model is

used, its implementation could be different.

AEP gross

[Gwh/y]

AEP with

wakes

[Gwh/y]

Wakes

losses [%]

WindSim

Eval. 7.0

136.1010 129.2864 5,01

OpenFOAM

and Octave

136.8124 131.9814 3,53

Test case 2: from Lucky Wind SpA

The considered site counts 12 turbines (600kW) deployed along the ridge;

Since the main wind direction is West-East wakes losses are very low.

For this case OF 3.0.1 has been used (some differences on settings compared to OF 2.3.1)

A detailed grid is designed, with snappyHexMesh

10/23

blockMesh + snappyHexMesh

11/23

blockMesh => boundary-fitted grid ok

blockMesh + snappyHexMesh with 2 levels and 2 cells per level


12/23

With the wall-functions counting for variable roughness

mapFields is used from structured mesh to mesh after snappyHexMesh

1. First meshing (blockMesh)

2. 1° level snappyHexMesh

3. 2° level snappyHexMesh

The goal is to achieve a variable heigth of the ground adjacent

cell, according to the roughness lenght z0 mapped at the site.

terrain.stl

nCellsBetweenLevels = 1 means

normal 2:1 refinement restriction,

larger means slower refinement.

nCellsBetweenLevels 1 and 2 have been tested


13/23

From SOWE 2015 (Crasto and Paraggio):

Reynolds Averaged Navier-Stokes (RANS)

Standard k-e turbulence model

Effects of model constant se on the wall-functions

Periodic BC

Mass flow given

0,000

0,005

0,010

0,015

0,020

0,025

0,030

0,035

0,040

0 5 10 15 20 25

z0 o

bta

ine

d b

y in

terp

ola

tio

n h

/2-1

00

m]

ratio first cell over roughness length (h/z0)

se 1.44

se 1.30

se 1.11

~11.8

Height of first (ground

adjacent) cell ~ 11.8 *

0.03m = 0.354m

Simulations 2D, rectangular domain

14/23

Standard k-e model simpleFoam (incompressible) First cell height 2m (= 66.67*z0) Convergence criteria based on residuals:

15/23

Residuals:

p 5e-4

U 1e-5

"(k|epsilon)" 1e-5

Further settings

Discretization schemes

16/23

divSchemes { default none; div(phi,U) bounded Gauss upwind; // bounded Gauss linearUpwind grad(U); div(phi,T) bounded Gauss upwind; div(phi,k) bounded Gauss upwind; // bounded Gauss linearUpwind grad(k); div(phi,epsilon) bounded Gauss upwind;// bounded Gauss linearUpwind grad(epsilon); div((nuEff*dev2(T(grad(U))))) Gauss linear; }

laplacianSchemes { default Gauss linear limited corrected 0.333; }

AEP computation

17/23

Assumed wind turbine rated power (kW): ............ 600

Averaged turbine power at reference (kW): ......... 228.059

AEP at reference (MWh): ........................... 1997.7971

AEP Park no wakes (MWh): .......................... 22430.0914

AEP Park wakes (MWh): ............................. 22209.2461

Capacity factor at reference (%): ................. 38.0098

Wakes losses (%): …................................ 0.98459

Power at each turbine computed at each sampling time (10 minutes).

To be compared against real SCADA data.

Power history

18/23

Ongoing the comparison against SCADA data with 10 min stepping.

A file containing the estimated average power for each turbine at each

time step.

X T03

X T04

○ Met Mast

X T05

X T12

X T01

X T02

Power history

19/23



time step.

X T03

X T04

○ Met Mast

X T05

X T12

X T01

X T02

Power history

20/23



time step.

X T03

X T04

○ Met Mast

X T05

X T12

X T01

X T02

~800m

Conclusions & ...

21/23

A new mesher has been developed to make a terrain fitted structured mesh OR a mesh over which run the snappyHexMesh; Possibility to deal with variable roughness; Post processing to compute AEP or power-histories; Wakes are accounted with a Jensen model

Conclusions & Future Steps

22/23

Comparison of predicted power history against SCADA data (on going); Probably need to improve the gridding to make a variable height of first cell; Run Bolund and other test cases; Stability (thermal effects); Coriolis; WAT export.

Aknowlodgements

23/23

The authors whish to thank the «Lucky Wind SpA» to provide the wind and production data for the test case 2.

energy yield assessment and site suitability using openfoam - crasto, castellani (sowe 2016)

Engineering