Validation of a Prediction Model for Control of Micro Wind Turbines

Georgia Institute of Technology komerath@gatech.edu

Validation of a Prediction Model for Control of Micro

Wind TurbinesRyan McGowan and Narayanan Komerath

Daniel Guggenheim School of Aerospace EngineeringGeorgia Institute of Technology

Atlanta, Georgia USA

INTERNATIONAL CONFERENCE ON POWER, SIGNALS, CONTROL AND COMPUTATIONSTrissur, India, January 3-06, 2012

SUMMARYAim

•Develop micro wind turbine for single-family use in India•Vertical axis vs. horizontal axis•Local manufacture & maintenance•Lifecycle safety & environment•Technically complex to design!

•Operation at low wind speeds•Low blade tip speed

Optimize design for low tip-speed ratio

TSR = Blade tip tangential\ Windspeed

•Aerodynamics simulation validated•Low Reynolds number corrections•Wind tunnel testbed

•Azimuthal modification strategy to improve operation•Real-time control options

Objective

Methods

Vertical Axis Wind Turbine

1. Bicycle-based 1m VAWT >270rpm, >70 w (mechanical)2. 2m 1kW VAWT for high coastal winds.

Issues: 1. Optimal tip speed ratio 2 to 5 – too high.2. Variable power transmission3. Nonlinear pitch control4. Flexible blade operation5. Benign failure modes6. Hybrid devices: power conditioning, storage

54-inch Horizontal Axis Wind Turbine Electrical Output vs. Wind Speed, with 50 Ohm resistive load (2 tests)

Horizontal Axis Wind Turbine Simulation: Power Coefficient vs. Tip Speed Ratio

Measured VAWT mechanical power in two tests vs. preliminary predictions from momentum streamtube theory.

40302010

Vt = - Vb

Vertical Axis Wind Turbine, looking from above, showing relative velocity on the Advancing Blade Side, and the blade wake.

Solidity, defined as diameter divided by blade chord times number of blades.

As solidity increases, blade-wake interaction increases.So we need Multiple StreamTube Theory to account for power loss from streamtubes due to power extraction or drag due to blades

Blade element predictions of the mechanical power output of the 3-armed, bi-bladed VAWT, for different choices of blade chord compared to the baseline chord, with fixed span

Aspect Ratio Effect on Optimal Tip Speed Ratio

Baseline AR =Span/chord. ~9

Power coefficient vs. tip speed ratio for various solidities (Sandia data and simulation)

Comparison of (GT) and Sandia performance predictions at a solidity of 0.18.

Positive Torque (driving) occurs when net force has a positivecomponent along the tangential direction, driving the blade

Tangential coefficient vs. alpha for a NACA 0015 airfoil

•Enable startup in low winds•Provide some power•Limit performance at high•speeds

• Passive control of local angle of attack• Eliminate blade stall/negative torque• Allow self-starting

Drag Channels

Guide Vanes

Passive Starting Mechanisms

To reach optimal TSR, one needs powered start

ConclusionsBegun to integrate prediction, design and testing of a 2m x 2m vertical axis wind turbine with slanted double blades.

Operating point predictions with multiple streamtube theory are validated against published results. Reynolds number effects are clearly seen in the predictions, and their proper inclusion allows the predictions to match experimental data well.

Low performance at Tip Speed Ratio <1 is as per predictions. Simulation used to study how to eliminate negative torque at low tip speed ratio.

A self-starting device using drag tubes isbeing simulated.

Limiting turbine speed for safety implies that high tip speed ratio is best achieved at low wind speeds by taking the turbine to operating speed using human pedaling action or an electric motor.

Time-resolved simulations and thus to control algorithms for adapting to given wind patterns and optimizing power extraction and safety.

ACKNOWLEDGEMENTS

The work reported in this paper was made possible by resources being developed for the “EXTROVERT” cross-disciplinary learning project under NASA Grant NNX09AF67G S01. Mr. Anthony Springer is the Technical Monitor.

Validation of a Prediction Model for Control of Micro Wind Turbines

Documents

DEVELOPMENT AND VALIDATION OF PREDICTION EQUATIONS …

PERFORMANCE PREDICTION OF GAS TURBINES … ABSTRACT Lappeenranta University of Technology Research papers 68 Juha Kaikko Performance Prediction of Gas Turbines by Solving a System

A Performance Prediction Model for Pumps as Turbines (PATs)

Trend Validation of CFD Prediction Results for Ship … Validation of CFD Prediction Results ... CFD Prediction Results for Ship Design ... influences in the regression analysis of

Derivation and validation of a clinical prediction rule

Frontiers of Turbulence Prediction · 2018. 9. 28. · Turbulence Prediction. Dissemination for Operational Use Diagnosis & Prediction. Validation & verification. Enhancement. Higher

Prediction of Runaway Characteristics of Kaplan Turbines

Under Water Explosion Pressure Prediction and Validation Using

PREDICTION AND VALIDATION OF CLOUDLESS ... 2006 Conference, American Solar Energy Society, Denver, CO (July 2006) PREDICTION AND VALIDATION OF CLOUDLESS SHORTWAVE IRRADIANCE SPECTRA

Off design performance prediction of steam turbines

Prediction of wind turbine noise and validation against ... · methods is important for the design of quiet wind turbines and for the planning of wind farms. Description of work A

Modified Maturity Offset Prediction Equations: Validation ... · Modiﬁed Maturity Offset Prediction Equations: Validation in Independent Longitudinal Samples of Boys and Girls Sławomir

Validation of TxDOT Flexible Pavement Skid Prediction ... · VALIDATION OF TXDOT FLEXIBLE PAVEMENT SKID PREDICTION MODEL: WORKSHOP . by . Arif Chowdhury . Assistant Research Engineer

MiR-155 Target Prediction and Validation in Nasopharyngeal ... · MiR-155 target prediction and validation in nasopharyngeal carcinoma Abstract MicroRNAs (miRNAs) play an important

Prediction and validation of shape distortions in the

Numerical prediction and experimental validation of impact

Climate Modelling, Climate Prediction and Model Validation

Development and validation of a clinical prediction tool

From validation to prediction: Lithospheric eld studies ... · Earth Planets Space, 56, 000Œ000, 2004 From validation to prediction: Lithospheric eld studies from Magsat to Swarm

Signal-To-Noise Ratio Prediction and Validation For Space