Melheim, Jens_CMR GexCon - Wind and wake modelling using...

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Wind and wake modelling using CFD Jens A. Melheim CMR GexCon Wind Power R&D seminar, 20-21 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 Navier-Stokes equations on a grid • Impractical to resolve the smallest time and length scales in a turbulent flow -> solve averaged or filtered Navier-Stokes equations – Need model for unresolved scales –> turbulence model • Use a finite volume formulation • Assume incompressible flow – Prediction-correction 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 Navier-Stokes equations after averaging/filtering – RANS: Reynolds Averaged Navier-Stokes • 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 – k-L, k-ε, k-ω • Reynolds stress models – Solve transport equations for 6 Reynolds stresses + dissipation rate of turbulent kinetic energy (ε) • Large eddy models – Solve filtered N-S 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=1-20 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=1-20 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 Navier-Stokes on axis-symmetric grid or 3D grid – ECN Wakefarmer, GH Windfarmer, FLaP (Uni Oldenburg) • Full CFD models – Model turbine by momentum sink – NTUA CFD, Ellipsys3D, CENER, CRES, RGU-3D-NS 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 96:103-122 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 near-field of the rotor are needed • Validation and benchmarking are key factors for success Slide 16 / 21.01.2011, Wind Power R&D Seminar, Trondheim ...
View Full Document

Ask a homework question - tutors are online