Dynamically Variable Blade Geometry for Wind Energy

Slides:



Advertisements
Similar presentations
Aerodynamics of Wind Turbine Control Systems By Chawin Chantharasenawong 21 August 2009.
Advertisements

Layout Optimisation Brings Step Change in Wind Farm Yield Dr Andrej Horvat, Intelligent Fluid Solutions Dr Althea de Souza, dezineforce Come and visit.
MAE 3241: AERODYNAMICS AND FLIGHT MECHANICS
Investigating the Use of a Variable-Pitch Wind Turbine to Optimize Power Output Under Varying Wind Conditions. Galen Maly Yorktown High School.
An Investigation into Blockage Corrections for Cross-Flow Hydrokinetic Turbine Performance Robert J. Cavagnaro and Dr. Brian Polagye Northwest National.
Vertical-Axis Wind Turbine Kang Zheng Aaron Peterson Mohd Ramjis.
A Methodology for a Decision Support Tool for a Tidal Stream Device
Theoretical & Industrial Design of Aerofoils P M V Subbarao Professor Mechanical Engineering Department An Objective Invention ……
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)
Next: Wind Turbine Rotors Goal ?. Question 1  Divergent thinking consists of A) Selection of unique answer B) Brainstorming many ideas.
1 Short Summary of the Mechanics of Wind Turbine Korn Saran-Yasoontorn Department of Civil Engineering University of Texas at Austin 8/7/02.
Douglas S. Cairns Lysle A. Wood Distinguished Professor
Wind Turbine Project Recap Wind Power & Blade Aerodynamics
Computational Modelling of Unsteady Rotor Effects Duncan McNae – PhD candidate Professor J Michael R Graham.
Experimental Aerodynamics & Concepts Group Micro Renewable Energy Systems Laboratory Georgia Institute of Technology Validation of.
Wind Modeling Studies by Dr. Xu at Tennessee State University
Power Generation from Renewable Energy Sources
Ted Light Jeff Robinson December 13, 2003
Jarred Morales and Cody Beckemeyer Advisior: Dr. Junkun Ma ET 483.
DUWIND, Delft University Wind Energy Institute 1 An overview of NACA 6-digit airfoil series characteristics with reference to airfoils for large wind turbine.
The Buhl High-Induction Correction for Blade Element Momentum Theory Applied to Tidal Stream Turbines Dr. Ian Masters (Swansea University) Dr. Michael.
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.
Energy in the Wind Walt Musial Senior Engineer National Wind Technology Center National Renewable Energy Laboratory Kidwind Teachers’ Workshop May 14,
Cody Beckemeyer Advisors: Junkun Ma Cris Koutsougeras ET 494 Fall 2013.
Wind Energy Program School of Aerospace Engineering Georgia Institute of Technology Computational Studies of Horizontal Axis Wind Turbines PRINCIPAL INVESTIGATOR:
Wind Power Energy Sources Fall Wind Potential Wind energy is the most abundant renewable energy source after solar 120 GW of peak world capacity.
1 Rotor Design Approaches Michael S. Selig Associate Professor Steady-State Aerodynamics Codes for HAWTs Selig, Tangler, and Giguère August 2, 1999  NREL.
Wind Engineering Module 4.1 Blade Element Theory
Wind Turbine Aerodynamics Section 2 – Power Control E-Learning UNESCO ENEA Casaccia - February Fabrizio Sardella.
ECE 7800: Renewable Energy Systems
Wind Turbine Aerodynamics Section 1 – Basic Principles E-Learning UNESCO ENEA Casaccia - February Fabrizio Sardella.
Wind Engineering Module 4.2 WT_PERF Analysis Lakshmi Sankar
Topic: Wind Turbine Activity Objective: ▫ Create, test, and improve wind turbine blades so that they create the largest possible voltage 1 Summary: ▫ Students.
Aerodynamics of Wind Turbines Part -3
Study of Separated Flow Over Low-Pressure Turbine Blades and Automobiles Using Active Flow Control Strategies Michael Cline Junior Mechanical Engineering.
NUMERICAL SIMULATION OF WIND TURBINE AERODYNAMICS Jean-Jacques Chattot University of California Davis OUTLINE Challenges in Wind Turbine Flows The Analysis.
2D Airfoil Aerodynamics
MODELING AND SIMULATION OF WIND TURBINE –DOUBLY FED INDUCTION GENERATOR (WT-DFIG) IN WIND FARM USE MATLAB/SIMPOWERSYSTEM Student : TRUONG XUAN LOC.
Power Generation from Renewable Energy Sources Fall 2012 Instructor: Xiaodong Chu : Office Tel.:
Wind power Part 3: Technology San Jose State University FX Rongère February 2009.
Supervisor: Dr David Wood Co-Supervisor: Dr Curran Crawford
Aerodynamic forces on the blade, COP, Optimum blade profiles
Wind Energy Program School of Aerospace Engineering Georgia Institute of Technology Computational Studies of Horizontal Axis Wind Turbines PRINCIPAL INVESTIGATOR:
Date of download: 5/31/2016 Copyright © ASME. All rights reserved. From: Aerodynamic Performance of a Small Horizontal Axis Wind Turbine J. Sol. Energy.
Water turbines Billy Gerena # Robert De Aza # 66880
MSC Software India User Conference 2012 September 13-14, 2012 Bangalore, India CFD Based Frequency Domain Flutter Analysis using MSC Nastran Ashit Kumar.
Vertical Axis Wind Turbine Noise
Turbine blade basics. Calculation of Wind Power Where P = power, measured in watts (W) or joules per second (J/s)  = density of fluid, measured in.
Wind Turbine Project Lift, Drag, Blade Aerodynamics & Power
Airfoil in a Wind Tunnel Experiment #6
Wind Turbine Project Recap Wind Power & Blade Aerodynamics.
Review of Airfoil Aerodynamics
Wind Turbine Control System
P M V Subbarao Professor Mechanical Engineering Department
Wind Turbine
Betz Theory for A Blade Element
MAE 3241: AERODYNAMICS AND FLIGHT MECHANICS
Actual Power Developed by A Rotor
Blade Design for Modern Wind Turbines
Date of download: 12/26/2017 Copyright © ASME. All rights reserved.
Off-design Performance of A Rotor
Fluid Dynamic Principles to Generate Axial Induction
Dynamic Controllers for Wind Turbines
Ashikaga Institute of technology JAPAN 〇Mitsumasa Iino
Design of Wind Turbines
Dual Induction theory for Wind Turbines
Eulerization of Betz theory: Wind Turbines
Layout Optimisation Brings Step Change in Wind Farm Yield
Micrositing for Wind Turbines
Presentation transcript:

Dynamically Variable Blade Geometry for Wind Energy Greg Meess, Michael Ross Dr. Ephrahim Garcia Laboratory for Intelligent Machine Systems AIAA Regional Student Conference Boston University April 23-24, 2010

Goal: Increase wind turbine energy output by morphing blade shape to match changing wind speeds. Pitch Chord Twist

Outline Motivation Experimental Design Airfoil Generation Simulation Optimization Results Geometry Power output

Motivation Wind turbines are constantly increasing in size Power output is proportional to rotor swept area The largest turbines cannot be built on land Blades are designed for higher wind speeds Maximize rated power Turbine spends little time operating at rated power Little focus on low wind speeds Variable Pitch http://www.terramagnetica.com/2009/08/01/why-are-wind-turbines-getting-bigger/

Problem Parameterization Blade Element Momentum (BEM) Theory is used Turbine has operating regime between 4 m/s and 20 m/s 4 m/s is lower limit of current turbines Fixed speed generator of 60 rpm Rotations vary from 30 to 120 rpm. Rayleigh Distribution is used to assess annual power output Chord, twist, and camber are examined Vestas V90 power output vs. wind speed Sample wind speed Rayleigh distribution

Airfoil Generation NACA XX12 Series XFOIL Simulation Leading edge, trailing edge follow NACA equations Flexible panels connect to leading edge, rest on trailing edge As chord extends/retracts, panels keep airfoil profile XFOIL Simulation CL, CD data collected for angles of attack between -10° and 45° NACA 2412 original, fully extended, and fully retracted shapes Sample data from XFOIL for modified shapes

Turbine Performance Analysis Equations based on basic BEM theory1, WT_Perf source code2, and Aerodyn Theory Manual3. Blade divided into a number of elements Power of each element is P= 1/2ρAU34a(1-a) Power Coefficient Cp = 4a(1-a) Axial induction factor defined as a = (U1-U2)/U1 Need initial guess for axial induction factor Axial induction factor calculated using relative wind angle, coefficients of lift and drag, tip loss factor Initial axial induction factor updated Iterate for convergence Calculate power Polyamide Streamtube around wind turbine rotor, used as basis for BEM theory (Manwell 85). Nylon “Kite Wing” 1 Manwell, J.F., et al., Wind Energy Explained, John Wiley & Sons Ltd., 2002. 2 Buhl, Marshall, National Renewable Energy Laboratory, 2004. 3 Laino, David and A. Hansen, User’s Guide to Wind Turbine Aerodynamics Software AeroDyn, Windward Engineering, 2002. Blade geometry for analysis of horizontal axis wind turbine (Manwell 108).

Parametric Study Performance of morphing blades compared to that of a fixed blade Sample blade from WT_Perf optimized across all parameters at wind speed of 10 m/s All morphing blades begin with this shape Each morphing blade changes one parameter Three chord scenarios are examined Extension only Extension and retraction Retraction only Add arrows

Optimization

Variable Pitch Low Speed Shape Morphology Plot 15° High Speed Shape

Variable Camber Add picture Morphology Plot

Annual Output Power Curve Highlight new lines

Variable Chord Low Speed Shape Define retraction factor High Speed Shape Emphasize retraction over others Morphology Surface

Highlight new lines

Variable Twist Low Speed Shape Morphology Surface High Speed Shape

Highlight new lines Clarification/vertical lines

Conclusion Cite “Fair”, “Good”,etc. Percent Improvement over Static Blade wind speed (m/s) retracting chord variable pitch variable twist variable camber Fair (6.7) 18.64% 23.54% 29.26% 21.77% Good (7.25) 15.51% 18.45% 23.71% 17.09% Excellent (7.75) 13.44% 14.98% 20.14% 13.79% Outstanding (8.4) 11.56% 11.60% 16.99% 10.47% Superb (10.45) 9.67% 7.51% 14.22% 6.16% Emphasize improvement over pitch Variable Twist has the most influence on the performance Consistent 5% improvement over current pitch control scheme Achievable using torque tube mechanism Shape distribution close to linear Find V-22 paper or illustration

Future Work

Acknowledgements Find official titles

Questions & Comments? Laboratory for Intelligent Machine Systems Acknowledgements: Professor Sidney Leibovich, Donald Barry