ABL layer

VestasFOAM 1.1.0 - LES/DES

Submitted by Yavor Hristov on May 5, 2015 - 12:00am
Main hypothesis

VestasFOAM 1.1.0 - DES is built upon the pimpleFoam solver packaged within the publically available OpenFOAM distribution [1]. The k-omega SST DES [2] turbulence model has been implemented in-house. If desired buoyancy can be selected through the Boussinesq approximation.

VestasFOAM - DES is used operationally to determine probability density functions of wind veer and wind shear and compliance with IEC standards for class A,B and C sites. This has been done with good success both forensically (i.e. once problems have been detected on old sites) and during the initial micro-siting activities when transient flow suspicions are raised on prospective sites.

VestasFOAM 1.1.0 - LES is built upon the SOWFA project led by NREL [3]. The SOWFA code has been modularized to fit within the VestasFOAM automated CFD workflows and linked to Vestas turbine libraries for efficient/automated case setup, execution and post-processing. Currently this is only valid on flat terrain/offshore.

For both LES/DES, grids are automatically generated in Pointwise [4] using a structured hyperbolic extrusion. Great care is taken to control grid quality, with small expansion ratios from terrain to rotor bottom, and uniform grid spacing through the turbine/wake areas. As with our steady process, when sufficiently vertically distanced from turbines, the horizontal mesh resolution is continually reduced in order to lower mesh size.

VestasFOAM 1.1.0 - Steady

Submitted by Yavor Hristov on May 5, 2015 - 12:00am
Main hypothesis

The basis of VestasFOAM is built upon the simpleFoam solver distributed with the publically available OpenFOAM release and suitable for steady, incompressible, turbulent and isothermal flows. This solver and associated k-epsilon turbulence model [2] have been expanded to include appropriate boundary conditions for ABL flow [3], Coriolis force, Durbin realizability constraint [4], extension to stratified flows as wells as canopy [5] and buoyancy source terms. Meshes are automatically generated with Pointwise [6] using structured hyperbolic extrusion ensuring the highest possible quality. In order to reduce the mesh size, the horizontal mesh goes through a step-wise reduction in resolution with height once sufficiently away from the terrain. This creates a hybrid mesh with "hanging-node" type architecture maximizing efficiency without sacrificing mesh quality near the terrain and turbines.

SOWFA - LES

Submitted by Matthew Churchfield on May 4, 2015 - 6:36pm
Main hypothesis

The large-eddy simulation (LES) solver within the Simulator for On/Offshore Wind Energy (SOWFA) is built upon the Open-source Field Operations And Manipulations (OpenFOAM) computational fluid dynamics (CFD) toolbox.  The solver is incompressible and uses the unstructured finite-volume formulation.  Buoyancy effects are included through a Boussinesq buoyancy forcing term.  Turbines are modeled with actuator lines.

EllipSys3D ABL

Tilman Koblitz's picture
Submitted by Tilman Koblitz on May 4, 2015 - 5:49pm
Main hypothesis

The EllipSys3D code is a multiblock finite volume discretization of the incompressible Reynolds Averaged Navier-Stokes (RANS) equations in general curvilinear coordinates.  The code uses a collocated variable arrangement, and Rhie/Chow interpolation [iv] is used to avoid odd/even pressure decoupling. As the code solves the incompressible flow equations, no equation of state exists for the pressure, and the SIMPLE algorithm of [v] is used to enforce the pressure/velocity coupling. The EllipSys3D code is parallelized with MPI for executions on distributed memory machines, using a non-overlapping domain decomposition technique.

The solution is advanced in time using a 2nd order iterative time-stepping (or dual time-stepping) method.  In each global time-step the equations are solved in an iterative manner, using under-relaxation. First, the momentum equations are used as a predictor to advance the solution in time.  At this point in the computation the flowfield will not fulfil the continuity equation. The rewritten continuity equation (the so called pressure correction equation) is used as a corrector making the predicted flowfield satisfy the continuity constraint.  This two step procedure corresponds to a single sub-iteration, and the process is repeated until a convergent solution is obtained for the timestep. When a convergent solution is obtained, the variables are updated, and we continue with the next timestep.

The three momentum equations are solved decoupled using a red/black Gauss-Seidel point solver. The solution of the Poisson system arising from the pressure correction equation is  accelerated using a multigrid method. In order to accelerate the overall algorithm, a three level grid sequence and local time stepping are used.

DWM

Submitted by Gunner Chr. Larsen on May 4, 2015 - 5:39pm
Main hypothesis

The basic philosophy is to consider wakes as passive tracers continuously emitted from the wind farm turbines. The basic idea is a split of scales in the wake flow field, based on the conjecture that large turbulent eddies are responsible for stochastic wake meandering only, whereas small turbulent eddies are responsible for wake deficit attenuation and expansion in the meandering frame of reference as caused by turbulent mixing.

Lillgrund Direction

Submitted by Matthew Churchfield on May 4, 2015 - 3:54pm

Scope

This document outlines three separate components of this benchmark.  It is the hope that the participant will simulate all three components, but the participant is free to simulate any or all of the components.

This benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is based on the actual operational Lillgrund wind farm in which there are multiple turbines interacting within an array.  The benchmark aims to test a wake/atmospheric model to reproduce the power production observed at Lillgrund when wind is from a southwesterly, southeasterly, and northwesterly sector. 

For the Southwest case, the sector is centered upon 222° aligned with rows A-H in which there is 4.3 rotor diameter (D) spacing.  For the Southeast case, the sector is centered upon 120° aligned with rows 1-8 in which there is a 3.3 D spacing.  For the Northwest case, the sector is centered upon the 300° direction aligned again with rows 1-8, with flow coming from the opposite direction of the Southeast case, with a 3.3 D spacing.

Lillgrund 360 Efficiency

Submitted by Matthew Churchfield on May 4, 2015 - 3:12pm

Scope

The benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is a case based on the actual operational Lillgrund wind farm in which there are multiple turbines interacting within an array.  This benchmark aims to test a wake/atmospheric model to reproduce the wind plant efficiency observed at Lillgrund over the full wind rose.

Objectives

Demonstrate how wake models perform and capture the wake formation and merging process in the presence of atmospheric shear and turbulence within a large modern wind farm composed of modern multimegawatt turbines. 

Data Accessibility

Brief description about the accessibility of the data

Input data

The conditions for simulating the Lillgrund_360_Efficiency case are:

Lillgrund TI Spacing

Submitted by Matthew Churchfield on May 4, 2015 - 3:09pm

Scope

The benchmark is open to participants of the Wakebench project using wake and, possibly, atmospheric boundary layer models. This is a case based on the actual operational Lillgrund wind farm in which there are multiple turbines interacting within an array.  This benchmark aims to test a wake/atmospheric model to reproduce the maximum power deficit of the second turbine in a row as a function of spacing and turbulence intensity.

Objectives

Demonstrate how wake models perform and capture the wake formation and merging process in the presence of atmospheric shear and turbulence within a large modern wind farm composed of modern multimegawatt turbines. 

Data Accessibility

The benchmark is offered to participants of the IEA Task 31 Wakebench.

Input data

The conditions for simulating the LillgrundTISpacing case are: