NUMERICAL SIMULATION OF WIND TURBINE AERODYNAMICS Jean-Jacques Chattot University of California Davis OUTLINE Challenges in Wind Turbine Flows The Analysis.

Slides:



Advertisements
Similar presentations
Aerodynamic Characteristics of Airfoils and wings
Advertisements

Lecture 8 – Axial turbines 2 + radial compressors 2
Delft University of Technology Aeroelastic Modeling and Comparison of Advanced Active Flap Control Concepts for Load Reduction on the Upwind.
AeroAcoustics & Noise Control Laboratory, Seoul National University
Lecture 7 – Axial flow turbines
A Computational Efficient Algorithm for the Aerodynamic Response of Non-Straight Blades Mac Gaunaa, Pierre-Elouan Réthoré, Niels Nørmark Sørensen & Mads.
The Ultimate Importance of Invariant Property : Rothalpy
The VAWT in Skew: Stereo-PIV and Vortex Modeling ir. C.J. Sim ã o Ferreira, M.Sc. K. Dixon, Dipl.-Ing. C. Hofemann, Prof. Dr. ir. G.J.W. van Bussel, Prof.
Performance Prediction and Design Optimization
Analysis of rotor wake measurements with the inverse vortex wake model Second PhD Seminar on Wind Energy in Europe October Risø National Laboratory.
A Methodology for a Decision Support Tool for a Tidal Stream Device
Steady Aeroelastic Computations to Predict the Flying Shape of Sails Sriram Antony Jameson Dept. of Aeronautics and Astronautics Stanford University First.
Design of Wind Turbines P M V Subbarao Professor Mechanical Engineering Department Selection of Optimal Geometrical & Kinematic Variables ….
Module 5.2 Wind Turbine Design (Continued)
1 Short Summary of the Mechanics of Wind Turbine Korn Saran-Yasoontorn Department of Civil Engineering University of Texas at Austin 8/7/02.
Wind Turbine Project Recap Wind Power & Blade Aerodynamics
Computational Modelling of Unsteady Rotor Effects Duncan McNae – PhD candidate Professor J Michael R Graham.
Dr. Sven Schmitz University of California, Davis Computational Modeling of Wind Turbine Aerodynamics and Helicopter Hover Flow Using Hybrid CFD Pennsylvania.
Design Process Supporting LWST 1.Deeper understanding of technical terms and issues 2.Linkage to enabling research projects and 3.Impact on design optimization.
Wind Modeling Studies by Dr. Xu at Tennessee State University
Where: I T = moment of inertia of turbine rotor.  T = angular shaft speed. T E = mechanical torque necessary to turn the generator. T A = aerodynamic.
Aerodynamics and Aeroelastics, WP 2
3D Dynamic Stall Modelling on the NREL phase VI Parked Blade ALVARO GONZALEZ XABIER MUNDUATE 47th AIAA Aerospace Sciences Meeting and Exhibit Orlando,
Basic Study of Winglet Effects
Introduction Aerodynamic Performance Analysis of A Non Planar C Wing using Experimental and Numerical Tools Mano Prakash R., Manoj Kumar B., Lakshmi Narayanan.
Smart Rotor Control of Wind Turbines Using Trailing Edge Flaps Matthew A. Lackner and Gijs van Kuik January 6, 2009 Technical University of Delft University.
Dynamically Variable Blade Geometry for Wind Energy
Energy in the Wind Walt Musial Senior Engineer National Wind Technology Center National Renewable Energy Laboratory Kidwind Teachers’ Workshop May 14,
Recent and Future Research for Bird-like Flapping MAVs of NPU Prof. B.F.Song Aeronautics School of Northwestern Polytechnical University.
Computational Studies of Horizontal Axis Wind Turbines Ph.D. Oral Defense Presented By Guanpeng Xu Advisor: Dr. L Sankar School of Aerospace Engineering.
Wind Energy Program School of Aerospace Engineering Georgia Institute of Technology Computational Studies of Horizontal Axis Wind Turbines PRINCIPAL INVESTIGATOR:
Wind Engineering Module 4.1 Blade Element Theory
Integrated Dynamic Analysis of Floating Offshore Wind Turbines EWEC2007 Milan, Italy 7-10 May 2007 B. Skaare 1, T. D. Hanson 1, F.G. Nielsen 1, R. Yttervik.
TOWER SHADOW MODELIZATION WITH HELICOIDAL VORTEX METHOD Jean-Jacques Chattot University of California Davis OUTLINE Motivations Review of Vortex Model.
Aerodynamics of Wind Turbines Part -3
Tim Fletcher Post-doctoral Research Assistant Richard Brown Mechan Chair of Engineering Simulating Wind Turbine Interactions using the Vorticity Transport.
HELICOIDAL VORTEX MODEL FOR WIND TURBINE AEROELASTIC SIMULATION Jean-Jacques Chattot University of California Davis OUTLINE Challenges in Wind Turbine.
UPWIND, Aerodynamics and aero-elasticity
1 Fluidic Load Control for Wind Turbine Blades C.S. Boeije, H. de Vries, I. Cleine, E. van Emden, G.G.M Zwart, H. Stobbe, A. Hirschberg, H.W.M. Hoeijmakers.
Wind power Part 3: Technology San Jose State University FX Rongère February 2009.
Challenges in Wind Turbine Flows
Supervisor: Dr David Wood Co-Supervisor: Dr Curran Crawford
Aerodynamic forces on the blade, COP, Optimum blade profiles
Evan Gaertner University of Massachusetts, Amherst IGERT Seminar Series October 1st, 2015 Floating Offshore Wind Turbine Aerodynamics.
Steps in Development of 2 D Turbine Cascades P M V Subbarao Professor Mechanical Engineering Department A Classical Method Recommended by Schlichting.……
Wind Energy Program School of Aerospace Engineering Georgia Institute of Technology Computational Studies of Horizontal Axis Wind Turbines PRINCIPAL INVESTIGATOR:
WIND TURBINE ENGINEERING ANALYSIS AND DESIGN Jean-Jacques Chattot University of California Davis OUTLINE Challenges in Wind Turbine Flows The Analysis.
Leakage Flows in Turbine Cascades P M V Subbarao Professor Mechanical Engineering Department In a Large Group, a Fraction of Parcels Will Try to Look for.
M. Khalili1, M. Larsson2, B. Müller1
Date of download: 6/1/2016 Copyright © ASME. All rights reserved. From: Numerical Simulation of the Aerodynamics of Horizontal Axis Wind Turbines under.
Purdue Aeroelasticity
Theory of Turbine Cascades P M V Subbarao Professor Mechanical Engineering Department Its Group Performance, What Matters.……
Wind Turbine Project Recap Wind Power & Blade Aerodynamics.
P M V Subbarao Professor Mechanical Engineering Department
UPWIND, Aerodynamics and aero-elasticity
Date of download: 10/29/2017 Copyright © ASME. All rights reserved.
DYNAMIC STALL OCCURRENCE ON A HORIZONTAL AXIS WIND TURBINE BLADE
P M V Subbarao Professor Mechanical Engineering Department
Betz Theory for A Blade Element
Blade Design for Modern Wind Turbines
SuperGen Assembly Cranfield University. 23rd Nov. 2016
Parallelized Coupled Solver (PCS) Model Refinements & Extensions
Rotors in Complex Inflow, AVATAR, WP2
Design and Analysis of Wind Turbines using Dynamic Stall Effects
Fluid Dynamic Analysis of Wind Turbine Wakes
Leakage Flows in Turbine Cascades
Purdue Aeroelasticity
VALIDATION OF A HELICOIDAL VORTEX MODEL WITH THE NREL UNSTEADY AERODYNAMIC EXPERIMENT James M. Hallissy and Jean-Jacques Chattot University of California.
Eulerization of Betz theory: Wind Turbines
Double-multiple Stream Tube Model for Darrieus Wind Turbines
Presentation transcript:

NUMERICAL SIMULATION OF WIND TURBINE AERODYNAMICS Jean-Jacques Chattot University of California Davis OUTLINE Challenges in Wind Turbine Flows The Analysis Problem and Simulation Tools The Vortex Model for Analysis and Design The Hybrid Approach Conclusion Stanford Tuesday, May 6, 2008

CHALLENGES IN WIND TURBINE FLOW ANALYSIS AND DESIGN Vortex Structure - importance of maintaining vortex structure R - free wake vs. prescribed wake models - nonlinear effects on swept tips and winglets High Incidence on Blades - separated flows and 3-D viscous effects Unsteady Effects - yaw, tower interaction, earth boundary layer Blade Flexibility

CHALLENGES IN WIND TURBINE FLOW ANALYSIS

THE ANALYSIS PROBLEM AND SIMULATION TOOLS Actuator Disk Theory (1-D Flow) Empirical Dynamic Models (Aeroelasticity) Vortex Models - prescribed wake + equilibrium condition - free wake - applied to design of blades for maximum power at given thrust on tower (including sweep and winglets) Euler/Navier-Stokes Codes - 10 M grid points, still dissipates wake - not practical for design

THE VORTEX MODEL FOR ANALYSIS AND DESIGN Goldstein Model Simplified Treatment of Wake -Rigid Wake Model -“Ultimate Wake” Equilibrium Condition -Base Helix Geometry Used for Steady and Unsteady Flows Application of Biot-Savart Law Blade Element Flow Conditions 2-D Viscous Polar

GOLDSTEIN MODEL Vortex sheet constructed as perfect helix with variable pitch

SIMPLIFIED TREATMENT OF WAKE - No stream tube expansion, no sheet edge roll-up (second-order effects) -Vortex sheet constructed as perfect helix called the “base helix” corresponding to zero yaw

“ULTIMATE WAKE” EQUILIBRIUM CONDITION Induced axial velocity from average power (iterations):

INFLUENCE OF WAKE ON RESULTS V Wind = 7m/s

BASE HELIX GEOMETRY USED FOR STEADY AND UNSTEADY FLOWS Vorticity is convected along the base helix, not the displaced helix, a first-order approximation

2-D VISCOUS POLAR

ANALYSIS RESULTS: STEADY FLOW Power output comparison

YAWED FLOW Time-averaged power versus velocity at different yaw angles =5 deg =10 deg =20 deg=30 deg

TOWER INTERFERENCE MODEL Simplified Model NREL Root Flap Bending Moment Comparison - Effect of Incoming Velocity V=5, 8 and 10 m/s - Effect of Yaw yaw=5, 10 and 20 deg

“UPWIND” CONFIGURATION

NREL ROOT FLAP BENDING MOMENT COMPARISON V=5 m/s, yaw=20 deg

DESIGN METHODOLOGY Minimize Torque Coefficient Thrust Coefficient is Lagrange multiplier

DESIGN METHODOLOGY Given “adv” – Given profile (2-D viscous polar) or corresponding to  Optimum circulation Design:

DESIGN TEST CASE Vortex Line Method (VLM) – Operating Points DESIGN AND ANALYSIS OF A ROTOR BLADE

HYBRID APPROACH Use Best Capabilities of Physical Models - Navier-Stokes for near-field viscous flow - Vortex model for far-field inviscid wake Couple Navier-Stokes with Vortex Model - improved efficiency - improved accuracy

Navier-Stokes Vortex Method Vortex Filament Biot-Savart Law (discrete) Boundary of Navier-Stokes Zone Converged for … Bound Vortex Coupling Methodology HYBRID METHODOLOGY

PCS/VLM COMPARISON Optimum Blade designed with VLM Power [kW] Torque [Nm] Bending Moment [Nm] Tangential Force [N] Thrust [N] PCSVLM Difference in Power : 0.84 %

RESULTS: STEADY FLOW NREL ROTOR Power output comparison

PCS/VLM COMPARISON PCS k-ω : Γ j VLM : c l VLM : Γ j PCS k-ω : c l

TRAILING VORTICITY NEAR PEAK POWER V Wind = 7m/sV Wind = 9m/s V Wind = 10m/sV Wind = 11m/s Trailing Vorticity is traceable with the spanwise velocity component at 5%-10% chord length downstream of the blade’s trailing edge. These complex 3D effects are very difficult to detect with ‘strip theory’. The PCS solver on the other hand is capable of disclosing such phenomena close to Peak Power.

CONCLUSIONS Vortex Model: simple, efficient, can be used for design Stand-alone Navier-Stokes: too expensive, dissipates wake, cannot be used for design Hybrid Model: takes best of both models to create most efficient and reliable simulation tool Next Frontier: aeroelasticity and multidisciplinary design

RECENT PUBLICATIONS S. H. Schmitz, J.-J. Chattot, “A coupled Navier-Stokes/Vortex- Panel solver for the numerical analysis of wind turbines”, Computers and Fluids, Special Issue, 35: (2006). S. H. Schmitz, J.-J. Chattot, “A parallelized coupled Navier- Stokes/Vortex-Panel solver”, Journal of Solar Energy Engineering, 127: (2005). J.-J. Chattot, “Extension of a helicoidal vortex model to account for blade flexibility and tower interference”, Journal of Solar Energy Engineering, 128: (2006). S. H. Schmitz, J.-J. Chattot, “Characterization of three-dimensional effects for the rotating and parked NREL phase VI wind turbine”, Journal of Solar Energy Engineering, 128: (2006). J.-J. Chattot, “Helicoidal vortex model for wind turbine aeroelastic simulation”, Computers and Structures, 85: (2007). S. H. Schmitz, J.-J. Chattot, “A method for aerodynamic analysis of wind turbines at peak power”, Journal of Propulsion and Power, 23(1): (2007). J.-J. Chattot, “Effects of blade tip modifications on wind turbine performance using vortex model”, AIAA (2008).

APPENDIX A UAE Sequence Q V=8 m/s  pitch=18 deg CN at 80%

APPENDIX A UAE Sequence Q V=8 m/s  pitch=18 deg CT at 80%

APPENDIX A UAE Sequence Q V=8 m/s  pitch=18 deg

APPENDIX B Optimum Rotor R=63 m P=2 MW

APPENDIX C Homogeneous blade; First mode

APPENDIX C Homogeneous blade; Second mode

APPENDIX C Homogeneous blade; Third mode

APPENDIX C Nonhomogeneous blade; M’ distribution

APPENDIX C Nonhomog. blade; EIx distribution

APPENDIX C Nonhomogeneous blade; First mode

APPENDIX C Nonhomogeneous blade; Second mode

APPENDIX C Nonhomogeneous blade; Third mode

TOWER SHADOW MODEL DOWNWIND CONFIGURATION