Wind Turbines Under Atmospheric Icing Conditions - Ice Accretion Modeling, Aerodynamics, and Control Strategies for Mitigating Performance Degradation

Transcription

1 The Pennsylvania State University The Graduate School Department of Aerospace Engineering Wind Turbines Under Atmospheric Icing Conditions - Ice Accretion Modeling, Aerodynamics, and Control Strategies for Mitigating Performance Degradation A Thesis in Aerospace Engineering by Dwight Brillembourg c 2013 Dwight Brillembourg Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science August 2013

2 The thesis of Dwight D. Brillembourg was reviewed and approved* by the following: Sven Schmitz Assistant Professor of Aerospace Engineering Thesis Advisor Dennis K. McLaughlin Professor of Aerospace Engineering George A. Lesieutre Professor of Aerospace Engineering Head of the Department of Aerospace Engineering *Signatures are on file in the Graduate School ii

3 Abstract This thesis presents a combined engineering methodology of ice accretion, airfoil data, and rotor performance analysis of wind turbines subject to moderate atmospheric icing conditions. The Turbine Icing Operation Control System (TIOCS) is based on strip theory for both ice accretion and aerodynamic modeling. The tool is valid for small amounts of accreted ice in the order of a few percent of the sectional airfoil chord. The TIOCS methodology is a fast engineering analysis tool for the wind industry and wind turbine operators that allows for finding guidelines for wind turbine operation during and post moderate icing events. In this thesis, the icing event was relatively short (less than an hour) and three control strategies were explored to determine wind turbine performance degradation. Preliminary results obtained for the NREL Phase VI rotor, the NREL 5MW rotor, and the in-house designed PSU-2.5 MW wind turbines subject to a representative icing condition indicate that performance degradation with respect to power loss can be mitigated with appropriate control strategies during and post an icing event. iii

4 Contents Page List of Figures List of Tables List of Symbols Acknowledgments vii xii xiv xvi Chapter 1 Introduction 1 Chapter 2 Ice Accretion Modelling - TIOCS TIOCS Objectives and Overview TIOCS Software: XTURB Blade Element Momentum Theory Momentum Theory Blade Element Theory Blade Element Momentum Theory Equations Prandtl s Root and Tip Loss Factor BEMT Solution Method Ice Accretion Software: LEWICE Icing Parameters Types of Ice Method of Updating Airfoil Aerodynamic Properties Subject to Ice Accretion Introduction Ice Shape Calculations Three Dimensional Lift and Drag Interpolation TIOCS Implementation Main TIOCS Routine XTURB Routine LEWICE Routine Iced Airfoil Performance Routine TIOCS: Software Architecture iv

5 2.8.1 TIOCS: Input Directory TIOCS: Output Directory TIOCS: Miscellaneous Directories Chapter 3 NREL Phase VI Results NREL Phase 6 Wind Turbine Parameters Atmospheric Icing Conditions Case 1: Baseline Operating Conditions during Icing Event Case 2: Wind Turbine Operation at a Higher Tip Pitch Angle and Decreased RPM Case 3: Parking the Wind Turbine with High Tip Pitch Angle Comparison Between Cases Validation of TIOCS Chapter 4 NREL 5 MW Results Atmospheric Icing Parameters NREL 5MW Wind Turbine Parameters Case 1: Baseline Operating Conditions during Icing Event Case 2: Wind Turbine Operation at a Higher Tip Pitch Angle and Decreased RPM Case 3: Parking the Wind Turbine with High Tip Pitch Angle Comparison Between Cases Validation of TIOCS Chapter 5 PSU 2.5MW Results Atmospheric Icing Parameters PSU 2.5MW Wind Turbine Parameters Case 1: Baseline Operating Conditions during Icing Event Case 2: Wind Turbine Operation at a Higher Tip Pitch Angle and Decreased RPM Case 3: Parking the Wind Turbine with High Tip Pitch Angle Comparison Between Cases Chapter 6 Summary and Conclusions 81 References 83 Appendix A Wind Turbine Configurations 86 A.1 NREL Phase VI A.2 NREL 5 MW A.3 PSU 2.5 MW Appendix B TIOCS Input Files 95 B.1 TIOCS Input File: User Setup B.1.1 TIOCS User Sub-Input File: Directory Sub-Input v

6 B.1.2 TIOCS User Sub-Input File: Blade Properties Sub-Input B.1.3 TIOCS User Sub-Input File: Output Files B.1.4 TIOCS User Sub-Input File: File Extensions B.2 TIOCS Input Files B.2.1 LEWICE Input Files B.2.2 XTURB Input Files B.2.3 Iced Airfoil Aerodynamics Input Files Appendix C TIOCS Output Files 117 C.1 TIOCS Output File: LEWICE C.2 TIOCS Output File: XTURB C.3 TIOCS Output File: TIOCS Appendix D TIOCS MATLAB Scripts 123 D.1 Start TIOCS Script D.2 TIOCS MAIN Script D.3 TIOCS Subroutines D.4 TIOCS Plotting Scripts D.5 TIOCS Output File Scripts vi

7 List of Figures Page 2.1 TIOCS Methodology Streamlines past the actuator disk as well as velocity and pressure upstream and downstream. [16] Streamlines past the rotating rotor disk. [17] Forces and moments on an airfoil section; α, angle of attack; c, airfoil chord [17] Schematic of blade elements; c, airfoil chord length; dr, radial length of element; r, radius; R, rotor radius; Ω, angular velocity of rotor [17] Blade Element Airfoil Forces; L lift force; D, drag force; φ blade flow angle; V 0 free stream velocity Local velocity triangle of a rotating blade section Helical wake pattern of single tip vortex [19] Total Loss Factor, F = F root F tip vs. r/r [20] BEMT iterative solution method [21] Sample Input File for LEWICE [13] Icing Severity [23] Glaze ice forming on a wind turbine blade Rime ice forming on a wind turbine blade Simulated Glaze Ice Shapes on the NLF-0414 as used by Kim and Bragg [25] Normal vector calculations on a clean S809 airfoil with an arbitrary ice shape Lift loss due to surface roughness (k/c = ) and simulated ridge ice (k/c = ): NACA 23012m and Re = 1.8E6 taken from Lee and Bragg [14] Drag gain due to surface roughness (k/c = ) and simulated ridge ice (k/c = ): NACA 23012m and Re = 1.8E6 taken from Lee and Bragg [14] Change in lift vs. angle of attack and ice location at k/c = for the ice shape shown in Figure Change in drag vs. angle of attack and ice location at k/c = for the ice shape shown in Figure Effect of simulated ridge ice of various heights at x/c = 0.10 location on the NACA 23012m: Re = 1.8E6 taken from Lee and Bragg [14] vii

8 2.22 Digitized plot of the effect of simulated ridge ice of various heights at x/c = 0.10 location on the NACA 23012m: Re = 1.8E6 taken from Lee and Bragg [14] Main TIOCS Routine XTURB Routine LEWICE Routine Iced Airfoil Performance Routine TIOCS Input Directory Architecture TIOCS Output Directory Architecture Chord Distribution of the NREL Phase VI Wind Turbine Blade Twist Distribution of the NREL Phase VI Wind Turbine Blade Lift Coefficient vs. Angle of Attack for the Re = 1.5E Drag Coefficient vs. Angle of Attack for the Re = 1.5E Nominal Power vs r/r for the NREL Phase VI at a wind speed of 7 m/s Nominal Thrust vs r/r for the NREL Phase VI at a wind speed of 7 m/s Case 1: Angle of Attack vs. Radial Location of the Clean and Iced NREL Phase VI at a wind speed of 7 m/s Case 1: Lift Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI at a wind speed of 7 m/s Case 1: Drag Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI at a wind speed of 7 m/s Case 1: Power vs. Radial Location of the Clean and Iced NREL Phase VI Case 1: Thrust vs. Radial Location of the Clean and Iced NREL Phase VI Case 2: Angle of Attack vs. Radial Location of the Clean and Iced NREL Phase VI Case 2: Lift Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI Case 2: Drag Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI Case 2: Power vs. Radial Location of the Clean and Iced NREL Phase VI Case 2: Thrust vs. Radial Location of the Clean and Iced NREL Phase VI Case 3: Bending Moment vs. Blade Tip Pitch Angle for the NREL Phase VI Case 3: Angle of Attack vs. Radial Location at various Tip Pitch Angles for the NREL Phase VI Case 3: Angle of Attack vs. Radial Location of the Clean and Iced NREL Phase VI Case 3: Lift Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI Case 3: Drag Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI Case 3: Power vs. Radial Location of the Clean and Iced NREL Phase VI Case 3: Thrust vs. Radial Location of the Clean and Iced NREL Phase VI Clean and Iced Airfoil Shapes for All Three Radial Locations Clean and Iced Airfoil Shapes for All Three Radial Locations Clean and Iced Airfoil Shapes for All Three Radial Locations viii

9 3.27 Clean: Torque [Nm] versus Approach Wind Speed [m/s] for the simulated NREL Phase VI rotor [28] [31] Iced: Torque [Nm] versus Approach Wind Speed [m/s] for the simulated NREL Phase VI rotor Iced: Torque Percent Power Loss versus Approach Wind Speed [m/s] for the simulated NREL Phase VI rotor Chord Distribution of the NREL 5MW Wind Turbine Blade Twist Distribution of the NREL 5MW Wind Turbine Blade Nominal Power vs r/r for the NREL 5MW Nominal Thrust vs r/r for the NREL 5MW Case 1: Angle of Attack vs. Radial Location of the Clean and Iced NREL 5MW Case 1: Lift Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Case 1: Drag Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Case 1: Power per unit span vs. Radial Location of the Clean and Iced NREL 5MW Case 1: Thrust per unit span vs. Radial Location of the Clean and Iced NREL 5MW Case 2: Angle of Attack vs. Radial Location of the Clean and Iced NREL 5MW Case 2: Lift Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Case 2: Drag Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Case 2: Power vs. Radial Location of the Clean and Iced NREL 5MW Case 2: Thrust vs. Radial Location of the Clean and Iced NREL 5MW Case 3: Bending Moment vs. Blade Tip Pitch Angle for the NREL 5MW Case 3: Angle of Attack vs. Radial Location at various Tip Pitch Angles for the NREL 5MW Case 3: Angle of Attack vs. Radial Location of the Clean and Iced NREL 5MW Case 3: Lift Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Case 3: Drag Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Case 3: Power vs. Radial Location of the Clean and Iced NREL 5MW Case 3: Thrust vs. Radial Location of the Clean and Iced NREL 5MW Clean and Iced Airfoil Shapes for All Three Radial Locations Clean and Iced Airfoil Shapes for All Three Radial Locations Clean and Iced Airfoil Shapes for All Three Radial Locations A Comparison of Power Coefficient versus Tip Speed Ratio between Homola et al. [4] and TIOCS Chord Distribution of the PSU 2.5MW Wind Turbine Blade Twist Distribution of the PSU 2.5MW Wind Turbine Blade Nominal Power vs r/r for the PSU 2.5MW Nominal Thrust vs r/r for the PSU 2.5MW Case 1: Angle of Attack vs. Radial Location of the Clean and Iced PSU 2.5MW.. 69 ix

10 5.6 Case 1: Lift Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Case 1: Drag Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Case 1: Power per unit span vs. Radial Location of the Clean and Iced PSU 2.5MW Case 1: Thrust per unit span vs. Radial Location of the Clean and Iced PSU 2.5MW Case 2: Angle of Attack vs. Radial Location of the Clean and Iced PSU 2.5MW Case 2: Lift Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Case 2: Drag Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Case 2: Power vs. Radial Location of the Clean and Iced PSU 2.5MW Case 2: Thrust vs. Radial Location of the Clean and Iced PSU 2.5MW Case 3: Bending Moment vs. Blade Tip Pitch Angle for the PSU 2.5MW Case 3: Angle of Attack vs. Radial Location at various Tip Pitch Angles for the PSU 2.5MW Case 3: Angle of Attack vs. Radial Location of the Clean and Iced PSU 2.5MW Case 3: Lift Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Case 3: Drag Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Case 3: Power vs. Radial Location of the Clean and Iced PSU 2.5MW Case 3: Thrust vs. Radial Location of the Clean and Iced PSU 2.5MW Clean and Iced Airfoil Shapes for All Three Radial Locations Clean and Iced Airfoil Shapes for All Three Radial Locations Clean and Iced Airfoil Shapes for All Three Radial Locations A.1 Chord and Twist Distribution for the NREL Phase VI Wind Turbine A.2 Lift and Drag Coefficient vs Angle of Attack for the S809 Airfoil A.3 Chord and Twist Distribution for the NREL 5 MW Wind Turbine A.4 Lift and Drag Coefficient vs Angle of Attack for the Cylinder01 Airfoil A.5 Lift and Drag Coefficient vs Angle of Attack for the Cylinder02 Airfoil A.6 Lift and Drag Coefficient vs Angle of Attack for the DU40 Airfoil A.7 Lift and Drag Coefficient vs Angle of Attack for the DU35 Airfoil A.8 Lift and Drag Coefficient vs Angle of Attack for the DU30 Airfoil A.9 Lift and Drag Coefficient vs Angle of Attack for the DU25 Airfoil A.10 Lift and Drag Coefficient vs Angle of Attack for the DU21 Airfoil A.11 Lift and Drag Coefficient vs Angle of Attack for the NACA64 Airfoil A.12 Chord and Twist Distribution for the PSU 2.5 MW Wind Turbine A.13 Lift and Drag Coefficient vs Angle of Attack for the Cylinder05 Airfoil A.14 Lift and Drag Coefficient vs Angle of Attack for the Cylinder04 Airfoil A.15 Lift and Drag Coefficient vs Angle of Attack for the Cylinder03 Airfoil A.16 Lift and Drag Coefficient vs Angle of Attack for the 00W2401DUT Airfoil A.17 Lift and Drag Coefficient vs Angle of Attack for the 00W2350DUT Airfoil A.18 Lift and Drag Coefficient vs Angle of Attack for the 97W300DUT Airfoil A.19 Lift and Drag Coefficient vs Angle of Attack for the 91W2250DUT Airfoil x

11 A.20 Lift and Drag Coefficient vs Angle of Attack for the 93W210DUT Airfoil A.21 Lift and Drag Coefficient vs Angle of Attack for the 95W180DUT Airfoil B.1 Example TIOCS Input File B.2 Example TIOCS Directory Sub-Input File B.3 Example TIOCS Sub-Input File B.4 Example TIOCS Sub-Input File B.5 Example TIOCS Sub-Input File B.6 Sample Input File for LEWICE [13] B.7 Sample Airfoil Polar File xi

12 List of Tables Page 2.1 Types of Ice NREL Phase VI Wind Turbine Parameters at V wind = 7m/s Icing Simulation Conditions Case 1: Performance degradation of the NREL Phase VI Rotor at V W ind = 7 m/s, RPM = 72 and Tip Pitch Angle = Case 2: Performance degradation of the NREL Phase VI Rotor at V W ind = 7 m/s, RPM = 36 and Tip Pitch Angle = Case 3: Performance degradation of the NREL Phase VI Rotor at V W ind = 7 m/s, RPM = 72 and Tip Pitch Angle = Thrust and Power Comparison of Case Radial Locations Analyzed for the NREL Phase VI Rotor, Nominal Case Icing Event Conditions Icing Simulation Conditions at V wind = 10m/s NREL 5MW Wind Turbine Parameters Case 1: Performance degradation of the NREL 5MW Rotor at V W ind = 10 m/s, RPM = and Tip Pitch Angle = Case 2: Performance degradation of the NREL 5MW Rotor at V W ind = 10 m/s, RPM = 6 and Tip Pitch Angle = Case 3: Performance degradation of the NREL 5MW Rotor at V W ind = 10 m/s, RPM = 6 and Tip Pitch Angle = Thrust and Power Comparison of Case Radial Locations Analyzed for the NREL 5MW Rotor, Nominal Case Icing Simulation Conditions Radial Locations Analyzed for the NREL 5MW Rotor, Homola et al. [4] Icing Simulation Conditions PSU 2.5MW Wind Turbine Parameters Case 1: Performance degradation of the PSU 2.5MW Rotor at V W ind = 12 m/s, RPM = and Tip Pitch Angle = xii

13 5.4 Case 2: Performance degradation of the PSU 2.5MW Rotor at V W ind = 12 m/s, RPM = 6.8 and Tip Pitch Angle = Case 3: Performance degradation of the PSU 2.5MW Rotor at V W ind = 12 m/s, RPM = and Tip Pitch Angle = Thrust and Power Comparison of Case Radial Locations Analyzed for the PSU 2.5MW Rotor, Nominal Case A.1 NREL Phase VI Wind Turbine Parameters A.2 NREL Phase VI Airfoil Locations A.3 NREL 5W Wind Turbine Parameters A.4 NREL 5 MW Airfoil Locations A.5 PSU 2.5W Wind Turbine Parameters A.6 PSU 2.5W Airfoil Locations xiii

14 List of Symbols β = Blade Twist Angle C d = Change in Sectional Drag Coefficient C l = Change in Sectional Lift Coefficient λ r = Local Tip Speed Ratio λ = Tip Speed Ratio Ω = Angular Velocity of Rotor ω = Angular Velocity of Wake Rotation φ = Blade Flow Angle ρ = Air Density σ = Blade Solidity σ = Local Solidity A = Rotor Disk Area a = Axial Induction Factor a = Angular Induction Factor c = Airfoil Chord Length C D = Lifting Body Drag Coefficient C d = Sectional Drag Coefficient C L = Lifting Body Lift Coefficient C l = Sectional Lift Coefficient C P = Power Coefficient C T = Thrust Coefficient D = Drag Force dq = Incremental Torque xiv

15 dr = Radial Length of Element dt = Incremental Thrust F = Prandtl s Total Loss Factor F root = Prandtl s Root Loss Factor F tip = Prandtl s Tip Loss Factor k/c = Ice Thickness L = Lift Force LW C = Liquid Water Content of the air in g/m 3 M V D = Median Volume Droplet [µm] N = Number of Blade Elements P inf = Ambient Static Pressure of the Air typically in Pascals [N/m 2 ] R = Rotor Radius r = Radial Location T inf = Ambient Temperature of the Air u = Velocity at the Rotor Disk u 1 = Velocity Downstream of the Rotor V 0 = Free Stream Velocity Upstream of the Rotor V rel = Relative velocity acting on a rotating airfoil section x/c = Ice Location on the Body xv

16 Acknowledgments I would like to thank my family, especially my mother, Monica, for their endless support and encouragement. They have inspired me to achieve my goals and more. I would like to express my gratitude towards my advisor Dr. Schmitz for giving me the opportunity to work on this research. With his guidance I have developed skills and knowledge that will stay with me throughout my career. I would also like to thank my thesis co-advisor, Dr. McLaughlin, for his assistance and support. xvi

17 Chapter 1 Introduction Wind energy is one of the most promising sources of renewable clean energy and is one of the fastest growing energy sources. As of 2012, the worldwide wind power capacity is at 44,800 MW with a 30% predicted growth rate in the upcoming decade [1]. Research in both wind turbine design as well as environmental and economic effects is necessary to maintain this growth. Developments in airfoil aerodynamics, structures, materials, gearbox and generator design, etc. has pushed the size of wind turbines from small-scale kilowatt machines up to today s multi-megawatt machines. However, it is no longer sufficient to design wind turbines with higher efficiencies and durable structures. Wind turbines today now face unique problems in three main climate zones: icy Nordic environments, humid regions that support large insect populations, and desert environments with sand-laden winds [2]. This thesis presents research of the problems faced in the icy Nordic environments, specifically, icing on wind turbine blades. The need for higher efficiency and greater power generation of modern day wind turbines has led to a shift in research of cooler climate wind energy. The advantage of offshore wind energy is that the wind is stronger off of the coasts and the higher densities of the air brought about by cooler temperatures. However, the higher wind speeds and higher density air of offshore wind has attributed to icing on wind turbine blades, which cause a detrimental effect on wind turbine efficiency. Makkonen et al. [3] stated that small amounts of ice on wind turbine blades deteriorate their aerodynamic performance and thus dramatically reduce the power generation by the turbine. Furthermore, large ice accretions may cause turbine vibrations and structural failure, and ice is hazardous when shed off the turbine blades. Homola et al. [4] ran a computer simulation of a moderate icing event on the NREL 5MW rotor and found that icing can lead to power losses between 24% and 27% due to airfoil performance degradation caused by ice. Jasinksi et al. [5] studied the effects of icing on airfoil performance in a wind tunnel experiment at the University of Illinois Urbana-Champaign. They studied predicted ice shapes using NASA LEWICE simulations and fabricated these ice shapes on a S809 airfoil [6]. They found that for a typical wind turbine rime ice shape with an ice thickness of 2.5% of the blade chord, the loss in power coefficient, C P, was 14.5%. These wind turbine performance predictions were obtained with Blade-Element Momentum Theory. They found that there was a 168.2% increase in the drag coefficient, C d, that correlated to the loss in the power coefficient. During a moderate to severe icing event, typically, a wind turbine is shut-down to minimize the amount of ice accretion and thereby reducing the negative effects caused by ice. However, this has been found to be cost-ineffective as a shut down of wind farms no longer produces any power. At 1

18 Norland in Norway, Byrkjedal and Vindteknikk [7] used the Weather and Research Forecase (WRF) code to study the wind power loss due to icing. They found that the annual icing time was approximately 1000 hours/year, and the Annual Energy Production (AEP) loss ranged between 14% and 28%. In order to harness the available wind energy in a cost-effective manner, a detailed study of wind turbine operation under different atmospheric conditions as well as the challenges and implications of these conditions on the performance is necessary [8]. Instead of a complete shutdown, the wind turbine could be operated under conditions, in which icing is not a factor in regards to power production as well as ice throw [9] [10]. While the attempts to study wind turbine icing are motivating, a detailed and efficient study is required to understand the performance degradation and devise real-time control mechanisms. Systematic performance evaluation of wind turbine airfoils under icing conditions needs to be conducted to provide a valuable database for modeling of wind turbine operation in cold climate regions [11]. In times of competing energy prices from other sources of energy, it is vital for the future competitiveness of wind energy to ensure availability of wind produced energy under adverse conditions such as moderate atmospheric surface icing. This thesis does not aim at predicting and evaluating the effects of ice prevention techniques such as blade surface coatings, heating elements, ultra-sound etc. The main objective is to understand the altered aerodynamic performance due to modified airfoil surface characteristics. The goal of this work is to provide the wind industry and wind developers with an engineering tool that can assist in evaluating wind turbine operation and control strategies that minimize the adverse effects of moderate wind turbine icing. 2

19 Chapter 2 Ice Accretion Modelling - TIOCS 2.1 TIOCS Objectives and Overview The Turbine Icing Operation Control System or TIOCS couples a blade-element momentum theory code, an ice accretion code, as well as an empirical methodology to predict aerodynamic properties of an iced airfoil shape. The blade-element momentum code is called XTURB and was developed at the Pennsylvania State University [12]. The ice accretion modeling code is called LEWICE [13] and was developed at NASA Glenn. Lastly, the method used to predict aerodynamic properties of ice shapes was developed by Bragg et al. [14]. TIOCS was written in MATLAB and couples XTURB, LEWICE, and the Bragg methodology in order to ice a wind turbine blade along different radial sections on the span of the blade. The basic routine is shown in Figure 2.1. Figure 2.1: TIOCS Methodology The primary goal of TIOCS is to accurately and quickly model ice accretion on a wind turbine blade. After the ice shape has been modeled, blade-element momentum theory will be used to analyze the performance degradation of the wind turbine. The code is designed to handle various atmospheric icing conditions as well as a multitude of different blade geometries. TIOCS needs to meet the following constraints: 3

20 1. TIOCS must be able to handle a multitude of different blade geometries and rotor properties. 2. TIOCS must be able to account for different angles of attack, relative velocities, airfoil shapes, and chord length along the span of the wind turbine blade to accrete ice. 3. TIOCS must be able to model the effects of ice on aerodynamic properties of an airfoil section quickly and accurately. 2.2 TIOCS Software: XTURB XTURB is capable of analyzing wind turbine blade designs under rotating and parked conditions subject to steady inflow. The code uses either classical Blade Element Momentum Theory (BEMT) or a Helicoidal Vortex Method (HVM) developed by Prof. J. J. Chattot at UC Davis for the prediction of blade loads [15]. Only BEMT was used to analyze the performance of the wind turbines in the results sections although the option to change this is left to the user Blade Element Momentum Theory Blade Element Momentum Theory or BEMT combines both momentum theory and blade element theory in order to describe the flow of fluids around rotor blades. Momentum theory is a control-volume analysis of forces based on the conservation of axial and angular momentum. Blade element theory is an analysis of forces at a blade airfoil section based on blade geometry Momentum Theory Momentum theory uses a combination of an actuator disk model as well as a rotor disk model. The main difference between the actuator and rotor disk models is that the actuator disk model does not include disk rotation while the rotor disk model does include disk rotation. The Actuator Disk Model Several assumptions need to be made in order to develop the actuator disk model: 1. The fluid flow is one-dimensional. 2. The flow is both inviscid and irrotational. 3. The rotor disk is not rotating. 4. The fluid flow is steady. Actuator disk theory describes the power extracted by the disk as solely a momentum loss of the flow. Figure 2.2 shows the streamlines past the actuator disk as well as the velocity and pressure 4

21 upstream and downstream [16]. Equation (2.1) relates the velocity at the rotor disk, u, with the free stream velocity, V 0, and the velocity downstream u 1. u = 1 2 (V 0 + u 1 ) (2.1) Figure 2.2: Streamlines past the actuator disk as well as velocity and pressure upstream and downstream. [16] The slowing of the velocity at the actuator disk can be described by the axial induction factor, a. Using the axial induction factor, Equation (2.1) can be rewritten as seen in Equation (2.2). u = (1 a)v 0 (2.2) Rotor thrust and power can also be calculated using the axial induction factor as follows: T = 2ρV 2 0 a(1 a)a (2.3) P = 2ρV 3 0 a(1 a) 2 A (2.4) where ρ is fluid density and A is the rotor disk area. Finally, dividing both Equations (2.3) and (2.4) by the available power in the wind, Equation (2.5), the thrust coefficient C T and the power coefficient C P can be found. The thrust coefficient and power coefficient are shown in Equations (2.6) and (2.7) respectively: 5

22 P wind = 1 2 ρv 3 0 A (2.5) C T = 4a(1 a) (2.6) C P = 4a(1 a) 2 (2.7) The Rotor Disk Model The assumptions of the rotor disk model are as follows: 1. The fluid flow is one-dimensional. 2. The flow is both inviscid and irrotational. 3. The fluid flow is steady. Unlike actuator disk theory, rotor disk theory assumes that the rotor disk is rotating. An illustration of the streamlines past the rotor disk is shown in Figure 2.3 taken from Manwell [17]. This rotation can be described using the angular induction factor, a, described in Equation (2.8) where ω is the wake rotation speed, and Ω is the rotor rotation speed. a = ω 2Ω (2.8) Figure 2.3: Streamlines past the rotating rotor disk. [17] In order to develop the equations in the Rotor Disk Model, several additional variables need to be introduced. The tip speed ratio, λ, is the ratio between the rotor tip speed and the free stream 6

23 velocity. The local tip speed ratio is defined as the fraction r/r of the actual tip speed ratio. The tip speed ratio and local tip speed ratio are presented in Equations (2.9) and (2.10) where R is the rotor radius and r is the radial location. λ = ΩR V 0 (2.9) λ r = λ r R Using the axial and angular induction factors as well as the local tip speed ratio and tip speed ratio, rotor power can be written as the following. P = λ Finally, the power coefficient can be found: Blade Element Theory 0 (2.10) 4πρa (1 a) 1 λ 2 V 3 0 R 2 λ 3 rdλ r (2.11) C P = 8 λ λ 2 a (1 a)λ 3 rdλ r (2.12) 0 Blade-Element Theory, also known as Strip Theory, analyzes the lift and drag forces on individual airfoil sections (blade elements) along the rotor blade. The forces and moments acting on a blade section airfoil can be seen in Figure 2.4, and the blade elements along the span of a rotor blade are illustrated in Figure 2.5. Figure 2.4: Forces and moments on an airfoil section; α, angle of attack; c, airfoil chord [17]. 7

24 Figure 2.5: Schematic of blade elements; c, airfoil chord length; dr, radial length of element; r, radius; R, rotor radius; Ω, angular velocity of rotor [17]. To develop the equations in Blade Element Theory, consider an airfoil section of a wind turbine blade shown in Figure 2.6. The blade flow angle, φ, is defined by Equation (2.13) where α is the angle of attack and β is the blade twist. φ = α + β (2.13) Figure 2.6: Blade Element Airfoil Forces; L lift force; D, drag force; φ blade flow angle; V 0 free stream velocity. Incremental thrust and torque for a single blade element can be found using Equations (2.14) and (2.15), respectively. dt = dlcosφ + ddsinφ (2.14) dq = (dlsinφ ddcosφ)r (2.15) 8

25 2.2.4 Blade Element Momentum Theory Equations Several assumptions need to be made in order to develop BEMT: 1. The fluid flow is two-dimensional. 2. There are losses at both the root and tip. 3. There is no radial flow. 4. The fluid flow is steady. Now that both momentum theory and blade element theory equations have been defined, the Blade Element Theory equations can now be developed. Describing both theories through the axial induction factor, a, the angular induction factor, a, and blade flow angle, φ, leads to Equations (2.16) and (2.17) for momentum theory and Equations (2.18) and (2.19) for blade element theory. dt = 4a(1 a)ρv 2 0 πrdr (2.16) dq = 4a (1 a)ρv 0 πr 3 Ωdr (2.17) dt = dlcosφ + ddsinφ (2.18) dq = (dlsinφ ddcosφ)r (2.19) To combine both the momentum theory equations and the blade element theories, the local velocity triangle needs to be defined. The local velocity triangle describes the velocities acting on an arbitrary rotating blade section shown in Figure 2.7 where V rel is the relative velocity acting on a rotating airfoil section. Figure 2.7: Local velocity triangle of a rotating blade section 9

26 Using the local velocity triangle in Figure 2.7, the following relationships can be established: tanφ = V 0(1 a) Ωr(1 + a ) = 1 a (1 + a )λ r (2.20) V rel = V 0(1 a) sinφ (2.21) dl = 1 2 ρc lvrel 2 cdr (2.22) dd = 1 2 ρc dvrel 2 cdr (2.23) Combining the momentum theory Equations (2.16) and (2.17), the blade element Equations (2.18) and (2.19) and the local velocity triangle relationship Equations (2.20) to (2.23) yield the sectional thrust and torque equations for BEMT: dt = B 2 ρv 2 rel (C lcosφ + C d sinφ)cdr (2.24) dq = B 2 ρv 2 rel (C lsinφ C d cosφ)crdr (2.25) where B stands for the blade number. By integrating the sectional thrust and torque from Equations (2.24) and (2.25), the thrust and power of the wind turbine a well as the thrust and torque coeffiecients can be found. The total thrust equation is shown in Equation (2.26), the thrust coefficient is shown in Equation (2.27), the total power is shown in Equation (2.28), and the power coefficient is shown in Equation (2.29) where N is the number of blade elements. T = N T (2.26) C T = N T 1 2 ρav 0 2 (2.27) P = N Q Ω (2.28) C P = N Q Ω 1 2 ρav 0 3 (2.29) 10

27 2.2.5 Prandtl s Root and Tip Loss Factor Helical vortices shed off of the root and tip of a wind turbine blade as shown in Figure 2.8. These vortices induce velocities that are not accounted for in BEMT and play a major role in losses of power production. Thus, in order to include three dimensional effects, Prandtl [18] introduced a correcting factor for these effects at the root and tip. There are limitations to Prandtl s root and tip loss factor. The total loss factor is only valid for lightly loaded rotors where the wake does not expand much. Also, the total loss factor is less accurate for less than three blades and for high tip speed ratios. Figure 2.8: Helical wake pattern of single tip vortex [19] The tip loss factor defined by Prandtl [18] is shown in Equation (2.30), and the root loss factor is shown in Equation (2.31). The total loss factor, F, is defined as the product of the root loss factor, F root, and the tip loss factor, F tip, seen in Equation (2.32). The total loss factor versus the radial location is presented in Figure 2.9. A total loss factor of one correlates to zero three-dimensional effects. Any total loss factor less than one introduces a penalty when computing the angular and axial induction factors in the BEMT solution method discussed below, which then reduces power production of the wind turbine. B 2 F tip = 2 (1 r/r) π cos 1 (exp[ ]) (2.30) (r/r)sinφ F root = 2 B π cos 1 2 (exp[ (r r root)/r ]) (2.31) (r root /R)sinφ F = F root F tip (2.32) 11

28 Figure 2.9: Total Loss Factor, F = F root F tip vs. r/r [20] BEMT Solution Method To analyze the performance of a wind turbine using BEMT, the following rotor parameters need to be known: blade number, chord distribution, twist distribution, airfoil distribution including aerodynamic data, blade radius, rotor RPM, and blade tip pitch angle. Given this information, the solution method shown in Figure 2.10 can be performed. Figure 2.10: BEMT iterative solution method [21] For each strip analyzed, the first step necessary is to guess the axial and angular induction factors. Typically, a value of 1/3 for the axial induction factor and a value of 0 for the angular induction factor are used. Using these values, the blade flow angle, φ, can be computed using Equation (2.20). The next step in the process is to calculate the angle of attack of the blade element using Equation (2.13). This angle of attack can be looked up using the blade element airfoil properties to find the associated lift and drag coefficients. The total loss factor may then be computed using Equations (2.30) to (2.32). Finally, the axial and angular induction factors are updated using Equations (2.34) and (2.35) below where σ is the local blade element solidity calculated from Equation (2.33). 12

29 σ = B c(r) 2πr (2.33) a = (1 + 4F sin 2 φ/[σ (C l cosφ + C d sinφ)]) 1 (2.34) a = ( 1 + 4F sinφcosφ/[σ (C l sinφ C d cosφ)]) 1 (2.35) If the updated axial and angular induction factors have converged, then continue on to the next blade element. If they have not converged, then continue the BEMT iterative solution process by using the updated axial and angular induction factors to find the new blade flow angle φ. Continue this process until all blade strips have converged and then calculate the rotor thrust and power coefficients using Equations (2.27) and (2.29) respectively. 2.3 Ice Accretion Software: LEWICE NASA Glenn Research Center developed an ice accretion code, LEWICE, for the analysis of aircraft in icing conditions. LEWICE contains an analytical ice accretion model that evaluates the thermodynamics of the freezing process that occurs when super-cooled droplets impact a body [13]. The model uses parameters of the icing event including the liquid water content (LWC), droplet size distribution, mean volumetric diameter (MVD), temperature, pressure, velocity, angle of attack, and chord length to calculate the ice shape on a body. LEWICE has four modules: flow field calculation, droplet trajectory calculation, thermodynamic and ice growth calculation, and geometry modification due to ice accretion [13]. First, the flow field is calculated with a potential flow solver for the clean body. A user-provided Navier-Stokes generated solution may be used in later versions of the code. Droplet trajectories are modeled with particle dynamics equations. The ice growth rate on each segment defining the surface is then determined by applying the thermodynamic model. The growth rate is correlated to a local ice thickness, and the body coordinates are adjusted to account for the accreted ice. This process is then repeated at the next time step, starting with a recalculation of the flow field over the iced geometry. The analysis ends when the user specified icing time has been reached. The length of each individual time step is automatically calculated or user-defined [13]. LEWICE has additional features, which was not used in the purposes of this thesis. A sample input file is shown in Figure

30 Figure 2.11: Sample Input File for LEWICE [13] 2.4 Icing Parameters The main icing parameters are ambient temperature, liquid water content (LWC), and mean volumetric diameter (MVD). The parameter with the most effect is temperature, and most icing tends to occur at temperatures between 0 and -20 [22]. Icing severity is indicated by the LWC and is normally expressed as grams of liquid water per cubic meter of air [22]. Figure 2.12 shows the four different categories in which icing severity is classified [23]. 14

31 Figure 2.12: Icing Severity [23] 2.5 Types of Ice Ice accretes on a body in various manners that heavily depends on temperature. LWC and relative velocities also contribute to the type of ice accretion. The two main types of ice are glaze ice and rime ice. Glaze ice or clear ice is characterized by smooth, transparent, and homogeneous ice coating occurring when freezing rain or drizzle hits a surface. Glaze ice usually occurs in regions where temperatures are near 0 C and droplets are relatively large. As a result, super-cooled liquid water striking the body does not freeze instantly on impact. As the droplet strikes the body it partially freezes and releases some latent heat. This latent heat, in combination with the kinetic temperature rise at the leading edge of the airfoil can cause some of the droplets to run back before freezing entirely. This creates a smooth, dense coating of ice, which can significantly reduce aerodynamic performance [24]. Figure 2.13 shows glaze ice accumulating on a wind turbine blade. 15

32 Figure 2.13: Glaze ice forming on a wind turbine blade Rime ice forms when small super-cooled water droplets impact the body and freeze on contact. Air becomes trapped between the frozen droplets producing a milky white appearance that is much easier to detect than clear ice. Rime is usually less dense than glaze ice and generally conforms to the airfoil leading edge which can reduce aerodynamic performance of the body [24]. Figure 2.14 shows rime ice accumulating on a wind turbine blade. Figure 2.14: Rime ice forming on a wind turbine blade Table 2.1 shows the typical temperatures in which the two main types of ice form. Table 2.1: Types of Ice Ice Type Temperature Glaze 0 C to -10 C Rime -15 C to -20 C 16

33 2.6 Method of Updating Airfoil Aerodynamic Properties Subject to Ice Accretion Introduction It was determined that potential flow codes such as JavaFoil, XFOIL, etc. could not resolve the complex geometry of an accreted ice shape. Instead of treating ice shapes generated by LEWICE as jagged and rough, the potential flow codes treated accreted ice as smooth. The ice shape geometry was treated as leading edge slats and improved upon airfoil aerodynamics and thus increased performance of the wind turbine blade. Therefore, another method needed to be used in order to determine the iced airfoil aerodynamics. Lee and Bragg [14] tested four airfoils with the same chord with simulated glaze ice. These airfoils were the NACA0012, NLF-014, NACA 23012, and the NACA 64A415. The NACA and the NACA 64A415 may be used as wind turbine airfoils. These simulated ice shapes had different ice shape heights, k/c, and were placed at different locations on the airfoil, s/c (or x/c) as can be seen in Figure Two-dimensional airfoil testing was performed in the University of Illinois 3x4 foot Wind Tunnel. Four 18 inch chord airfoils were tested, but only the results of the NACA 23012m airfoil was used in this paper. Lee and Bragg [14] produced several polar plots of changes in lift and drag at various angles of attack, ice location x/c, and ice thickness k/c. These plots were digitized, and ice shape parameters were calculated on ice shapes produced by LEWICE. These parameters were then used to interpolate changes in lift and drag from the digitized plots. Several assumptions needed to be made in order to simplify lift and drag data taken from Lee and Bragg [14]. The ice shapes that were produced are considered quarter round, and the change in lift and drag are acting at a Reynolds number of 1.8E6. It has been determined by Lee and Bragg [14] that changes in lift in drag are independent of both ice shape geometry and Reynolds number and therefore these assumptions are valid. 17

34 Figure 2.15: Simulated Glaze Ice Shapes on the NLF-0414 as used by Kim and Bragg [25] Ice Shape Calculations A MATLAB script was written in order to calculate the ice shape parameters, according to Lee and Bragg [14], produced from LEWICE. The methodology involved in calculating both ice shape location x/c, and ice thickness k/c, is as follows. Normal vectors were calculated off of the clean airfoil shape using a circular approximation seen in Appendix A. Circular Approximation. The intersection point between these normal vectors and the iced airfoil shape were then calculated. Finally, the length of each normal vector was computed, and the maximum length was assumed to be k/c. The x value associated with the maximum normal vector length was assumed to be x/c. Figure 2.16 shows an example normal vector calculation on a clean S809 airfoil with an arbitrary ice shape. The normal vectors calculated off of the clean S809 airfoil are shown in black. The computed maximum normal vector is shown in magenta. This ice shape is used in calculations of lift and drag in the following section. 18

35 Figure 2.16: Normal vector calculations on a clean S809 airfoil with an arbitrary ice shape Three Dimensional Lift and Drag Interpolation After x/c and k/c were calculated on an ice shape using the MATLAB script, these values were used in order to find associated changes in lift and drag. To update the associated values of drag and lift, dcl and dcd values were taken from Lee and Bragg [14]. Figure 2.17 shows the change in lift on the NACA 23012m with an ice shape of k/c = and k/c = at a Reynolds number of 1.8E6 and Figure 2.18 shows the change in drag. These plots were digitized along with figures taken from Bragg and Loth [26] to calculate the change in lift and drag for an ice shape at an angle of attack between 0 and 8 degrees. 19

36 Figure 2.17: Lift loss due to surface roughness (k/c = ) and simulated ridge ice (k/c = ): NACA 23012m and Re = 1.8E6 taken from Lee and Bragg [14]. Figure 2.18: Drag gain due to surface roughness (k/c = ) and simulated ridge ice (k/c = ): NACA 23012m and Re = 1.8E6 taken from Lee and Bragg [14]. Using the digitized plots, a surface plot can be made that relates changes in lift and drag as a function of angle of attack, ice location x/c, and ice thickness k/c. Figure 2.19 and Figure 2.20 show the change in lift and drag at an ice thickness of k/c =

37 Figure 2.19: Change in lift vs. angle of attack and ice location at k/c = for the ice shape shown in Figure Figure 2.20: Change in drag vs. angle of attack and ice location at k/c = for the ice shape shown in Figure Using the experimental data to find the change in lift and drag, the lift and drag for an arbitrary ice shape can now be computed using Equation 2.36 and C l,iced = C l,clean C l (2.36) C d,iced = C d,clean + C d (2.37) 21

38 The original lift vs. alpha curve for the NACA 23012m airfoil is shown in Figure This plot was digitized and the replica plot is shown in Figure Note that the digitized plot only contains data for angles of attack between 0 and 8 degrees due to lack of change in lift and drag coefficient data. Figure 2.21: Effect of simulated ridge ice of various heights at x/c = 0.10 location on the NACA 23012m: Re = 1.8E6 taken from Lee and Bragg [14]. Figure 2.22: Digitized plot of the effect of simulated ridge ice of various heights at x/c = 0.10 location on the NACA 23012m: Re = 1.8E6 taken from Lee and Bragg [14]. 22

39 2.7 TIOCS Implementation TIOCS is broken down into four different components: 1. Program Inputs: Necessary inputs are the XTURB input file, LEWICE Input file, TIOCS input file, airfoil coordinates, clean airfoil polar data, and the iced airfoil sectional lift and drag files. 2. BEMT Module: TIOCS calls the external executable file xturb.exe with either clean aerodynamic data or with iced aerodynamic data. The increase in chord length due to ice is automatically updated in the XTURB input file. 3. LEWICE Module: TIOCS calls the external executable lewice.exe with either the clean airfoil coordinate file or the iced airfoil coordinate file (depending on the iteration number) for each radial station specified by the user. Angles of attack, chord length, and relative velocity for each radial station are taken from the previous XTURB run. 4. Iced Airfoil Performance: TIOCS uses experimental data from Bragg et al. [14] in order to update the iced sectional lift and drag coefficients. All inputs listed above are discussed in further detail below. 23

40 2.7.1 Main TIOCS Routine The main TIOCS routine (MAIN TIOCS.m) shown in Appendix D ties all of the modules together. The flow chart of the main TIOCS routine is shown in Figure 2.23: Main TIOCS Routine XTURB Routine The XTURB Routine is the module that runs BEMT on the wind turbine blade. The routine moves the associated airfoil polar files, writes the XTURB input file, calls XTURB, and then copies the XTURB output files into the TIOCS Output Directory. The XTURB Routine flow chart is shown in Figure Figure 2.24: XTURB Routine 24

41 2.7.3 LEWICE Routine The LEWICE Routine is the module that ices each radial section airfoil. The routine moves the airfoil coordinates file to the lewice.exe directory and writes the LEWICE input file using the angle of attack, chord length, and relative velocity extracted from XTURB. The LEWICE Routine flow chart is shown in Figure Figure 2.25: LEWICE Routine Iced Airfoil Performance Routine The Iced Airfoil Performance Routine is the module that calculates the updated airfoil polar files using the method described in Section 2.6. The LEWICE Routine flow chart is shown in Figure

42 Figure 2.26: Iced Airfoil Performance Routine 2.8 TIOCS: Software Architecture TIOCS is setup with two distinct Input and Output Directories as well as a set of miscellaneous directories. The user has flexibility in regards to renaming the directories but otherwise, the main architectures are fixed TIOCS: Input Directory TIOCS Input Directory contains 3 sub directories as well as the 4 different files shown in Figure 2.27 that are described below: 1. Setup Directory: Parent of all the TIOCS input files. 2. Input Files: The main input files necessary to run LEWICE, XTURB, and TIOCS (lewice.inp,xturb.inp,tiocs.inp) are contained in the Setup Directory. The TIOCS MATLAB start up script (StartTiocs.m) is also contained in this folder. See Appendix B for information. 3. Iced Airfoil Delta Directory: Contains the change in lift and drag coefficients text files (DCL.txt and DCD.txt). 26

43 4. Airfoil Coordinates Directory: Contains the airfoil coordinates files with file extension specified in TIOCS.inp. Note that TIOCS uses the xturb.inp file variable AIRFDATA to determine the airfoil names; any other files in this folder will be ignored to allow the user to create a database of airfoil coordinates. The airfoil name must match the polar file name. For example [Airfoil Name].[Polar File Extension] must match [Airfoil Name].[Airfoil Coordinate File Extension]. 5. Polar File Directory: Contains all airfoil polar file data associated with the AIRFDATA variable name in the XTURB input file. Any extra files in this folder will be ignored if they do not match the airfoil name. Figure 2.27: TIOCS Input Directory Architecture TIOCS: Output Directory The architecture of the Output Directory is more complicated than that of the Input Directory. However, TIOCS automates the generation of the Output Directory and its sub-directories so minimal action is required by the user. The Output Directory Architecture is shown in Figure The Output Directory contains three children that each have their own children as well. Each directory is described below: 1. Output Directory: contains all of the outputs generated by TIOCS. The Output Directory location and name are specified by the user. 2. Clean Rotor Directory: the Clean case before the icing event is initialized. TIOCS calls XTURB using the XTURB input file and associated airfoil polar files and writes these as 27

44 well as XTURB output files in this directory. The Clean Rotor Directory contains three children (XTURB Input File Directory, XTURB Output File Directory, and XTURB Plot Directory) described below. 3. XTURB Input File Directory: contains all of the files used to run XTURB (XTURB input file and associated polars). 4. XTURB Output File Directory: contains all of the output files generated from the input files specified in the XTURB Input File Directory located in the parent directory. 5. XTURB Plot Directory: TIOCS generates plots using the data located in the XTURB Output File Directory and saves them here. 6. Iced Rotor Directory: contains an XTURB Input, Output, and Plot Directory. In addition, after the Clean case is run, the icing event starts. TIOCS automatically generates a varying amount of folders associated with the radial stations specified by the user. Each of these radial station folders contain local airfoil station data. There are four files stored here as well as a Figures directory specified below. i. The first file is the iced airfoil coordinate file generated by LEWICE called final1.dat. ii. The second is an output file generated by TIOCS in which the iced airfoil parameters discussed in Section 2.6 are calculated. iii. The third is an output file generated by TIOCS in which the clean polar files are updated using data from Bragg et al. [14]. iv. The fourth file is the LEWICE input file used to generate final1.dat. v. Figures Directory: TIOCS generates plots of the data contained its parent Radial Station Directory. 7. Iced Nominal Case Directory: After the icing event is completed, XTURB is run one last time using the nominal settings specified in the TIOCS input file. This is done to allow the user to run the wind turbine during an icing event in any manner he/she may choose and analyze the predicted performance degradation. It further contains an XTURB Input, Output, and Plot Directory that contain all of the XTURB iced nominal case data. 8. General Performance Degradation Output Files: three different output files are generated about the overall icing event. These will be discussed in detail. 28

45 Figure 2.28: TIOCS Output Directory Architecture TIOCS: Miscellaneous Directories There are two final directories that cannot be classified under input or output. The two directories are Code Directory and the TIOCS MATLAB Script Directory described below: 1. Code Directory: the path to this director is specified by the user in the TIOCS.inp file. This directory contains the executable files for LEWICE and XTURB. The LEWICE executable must be named lewice.exe and the XTURB executable must be named xturb.exe. Note that these names are case sensitive. 2. TIOCS MATLAB Script Directory: the path to this director is specified by the user in the TIOCS.inp file. This directory contains all of the MATLAB.m files used by TIOCS. 29

46 Chapter 3 NREL Phase VI Results 3.1 NREL Phase 6 Wind Turbine Parameters The NREL Phase VI rotor is a two-bladed stall-controlled wind turbine rated at 20 kw of power. The wind turbine parameters as used in this analysis are shown in Table 3.1. The rotor has a linear chord distribution as shown in Figure 3.1 and only uses the S809 airfoil. The twist distributions can be seen in Figure 3.2. The chord and twist distribution are based on the S809 profile described by Giguère et al. [5]. See Appendix A.1 for more information on the NREL Phase VI rotor. Although the NREL Phase VI rotor is stall-controlled, pitch-control was assumed possible for this wind turbine for TIOCS validation purposes. Table 3.1: NREL Phase VI Wind Turbine Parameters at V wind = 7m/s Blade Number 2 Blade Radius [m] 5.03 Rotor RPM 72 Blade Tip Pitch [deg] 3 Wind Speed [m/s] 7 Power [W] 5692 Thrust [N] 1120 Power Coefficient Thrust Coefficient

47 Figure 3.1: Chord Distribution of the NREL Phase VI Wind Turbine Blade Figure 3.2: Twist Distribution of the NREL Phase VI Wind Turbine Blade As mentioned, the NREL Phase VI rotor exclusively uses the S809 along the entire blade span. The original clean lift and drag polars used in the TIOCS methodology are presented in Figures 3.3 and

48 Figure 3.3: Lift Coefficient vs. Angle of Attack for the Re = 1.5E6 Figure 3.4: Drag Coefficient vs. Angle of Attack for the Re = 1.5E6 The nominal power and thrust versus radial location can be seen in Figures 3.5 and 3.6 and were calculated in TIOCS using thrust and torque coefficients calculated by XTURB. As shown, the majority of the power and thrust produced by the wind turbine occurs at r/r 0.6. This is also where icing is expected to occur due to smaller chord length as well as increased relative velocity, V rel, with respect to the inboard sections. 32

49 Figure 3.5: Nominal Power vs r/r for the NREL Phase VI at a wind speed of 7 m/s Figure 3.6: Nominal Thrust vs r/r for the NREL Phase VI at a wind speed of 7 m/s 3.2 Atmospheric Icing Conditions Three different cases were run in TIOCS for the NREL Phase VI during the icing event described in Table 3.2. The first case was running the wind turbine during an icing event without altering the wind turbine parameters in Table 3.1. The second case was running the wind turbine during an icing event at a slower RPM and a higher tip pitch setting than the nominal. The third case was running the wind turbine during an icing event in the parked condition at high tip pitch 33

50 angle relative to the nominal tip pitch. The purpose of these three different cases was to determine if it is more beneficial in the long run to stop running a wind turbine during an icing event or to continue running and attempt to accrete ice in a more tactful manner, i.e. accreting ice along the camber line of the airfoil, accreting less ice, etc. All cases were run for 21 different radial locations shown in Appendix A.1. Table 3.2: Icing Simulation Conditions Icing Event Time [sec] 600 Droplet Size, MVD [µm] 20 Liquid Water Content, LWC [g m 3 ] 0.50 Air Temperature [ C] -3 Atmospheric Pressure [N m 2 ] Case 1: Baseline Operating Conditions during Icing Event The NREL Phase VI wind turbine was run under normal operating conditions from Table 3.1 during a 10 minute icing event as described in Table 3.2. Table 3.3 presents an analysis of the performance degradation of the NREL Phase VI at a wind speed of 7 m/s. The rotor thrust extracted under nominal operation of the rotor is 1120 N while it is 977 N under the icing condition; a decrease of 12.8%. The thrust loss is not a problem in wind turbine operation, however, the power extracted under nominal operation of the rotor is 5692 W compared to 4419 W under icing conditions; a loss of 22.4%. Table 3.3: Case 1: Performance degradation of the NREL Phase VI Rotor at V W ind = 7 m/s, RPM = 72 and Tip Pitch Angle = 3. NREL Phase VI Thrust [N] Power [W] Nominal Case Percent Loss 12.8% 22.4 % An analysis as to explain the loss in thrust and power is as follows. The angle of attack distribution along the blade for both the Nominal (Clean) and Case 1 (Iced) settings are presented in Figure 3.7 and was taken from XTURB. After the icing event, the angle of attack of the wind turbine increases due to the newly accreted ice. This increase in angle of attack as well as in icing parameters alter the lift and drag coefficients along the entire blade span. An analysis of individual blade sections will be presented later. The lift coefficient versus radial location is shown in Figure 3.8, and the drag coefficient versus radial location is shown in Figure

51 Figure 3.7: Case 1: Angle of Attack vs. Radial Location of the Clean and Iced NREL Phase VI at a wind speed of 7 m/s Figure 3.8: Case 1: Lift Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI at a wind speed of 7 m/s 35

52 Figure 3.9: Case 1: Drag Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI at a wind speed of 7 m/s The decrease in lift and the increase in drag calculated by XTURB reduces both the thrust and power production of the NREL Phase VI when compared to the baseline case without ice. Both sectional power and thrust versus blade span are shown in Figures 3.10 and 3.11 respectively. It can be concluded that running the wind turbine at its baseline operating conditions is not a practical way to conserve power in the long run. Figure 3.10: Case 1: Power vs. Radial Location of the Clean and Iced NREL Phase VI 36

53 Figure 3.11: Case 1: Thrust vs. Radial Location of the Clean and Iced NREL Phase VI 3.4 Case 2: Wind Turbine Operation at a Higher Tip Pitch Angle and Decreased RPM The second scenario that was explored was running the wind turbine at a higher tip pitch angle and decreasing the rotor RPM when compared to the nominal case. Instead of parking the wind turbine, running the wind turbine at a higher tip pitch angle and lower RPM will still produce power while keeping the angle of attack of the wind turbine lower when compared to the nominal case. Also, running at a decreased RPM will reduce the tip speed and thus, the amount of accreted ice. For this case, the rotor RPM was decreased to 36, half of its nominal RPM. To find the tip pitch to run for this case, the tip pitch was increased until the angle of attack was lower than the nominal case and the wind turbine still produced at least a fifth of its rated power. The effect of leading edge ice reduces the lift and drag penalty when compared to ice accretion off of the leading edge [14]. The NREL Phase VI rotor was run using the optimum pitch angle, which was found to be 20 and at half of its nominal RPM of 36 during the icing event at a wind speed of 7 m/s. After the icing event was completed, the wind turbine was set back to its nominal tip pitch angle of 3 and nominal RPM of 72, and BEMT was run again at a wind speed of 7 m/s. The performance of the NREL Phase VI run under Case 2 is shown in Table 3.4. As seen, there was only a 2.6% loss in thrust and more importantly, a 6.9% loss in power after the icing event was complete. 37

54 Table 3.4: Case 2: Performance degradation of the NREL Phase VI Rotor at V W ind = 7 m/s, RPM = 36 and Tip Pitch Angle = 20. NREL Phase VI Thrust [N] Power [W] Nominal Case Percent Loss 2.6% 6.9 % Figures 3.12 to 3.14 show the angle of attack, lift coefficient, and drag coefficient along the blade span. As shown, the angle of attack does not change when compared to the nominal case and because of this, the lift coefficient does not decrease significantly from the nominal case either. However, drag does increase especially in the outboard sections. This is because ice buildup has a larger effect on smaller outboard airfoil chords than that of the larger inboard airfoil chords [27]. This mainly due to the decrease in collection efficiency of the droplets with the blade and the reduction in relative velocity [4]. Figure 3.12: Case 2: Angle of Attack vs. Radial Location of the Clean and Iced NREL Phase VI 38

55 Figure 3.13: Case 2: Lift Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI Figure 3.14: Case 2: Drag Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI The decrease in lift and the increase in drag reduces both the thrust and power production of the NREL Phase VI when compared to the baseline case, however not by much. Both power versus radial location and thrust versus radial location are shown in Figures 3.15 and 3.16, respectively. At the inboard sections (r/r < 0.6), there was little to no change in power production. Most of the power loss occurred near the outboard sections of the blade (r/r 0.6). It can be concluded that running the wind turbine normally during this particular icing event is a more practical way to run the wind turbine when compared to Case 1. 39

56 Figure 3.15: Case 2: Power vs. Radial Location of the Clean and Iced NREL Phase VI Figure 3.16: Case 2: Thrust vs. Radial Location of the Clean and Iced NREL Phase VI 3.5 Case 3: Parking the Wind Turbine with High Tip Pitch Angle The last scenario that was explored was parking the wind turbine with a high tip pitch angle relative to the nominal tip pitch during the icing event described in Table 3.2. For this scenario, the optimum tip pitch angle needed to calculated before this case could be run. The optimum tip pitch angle is defined as the blade pitch angle that produced the minimum bending moment while the wind turbine was parked if the angle of attack remained fairly small along the entire blade 40

57 span. This minimum bending moment correlates to the tip pitch angle that brings the angle of attack of the wind turbine closest to zero. The reason this was done was because ice accretion on the leading edge of an airfoil has the least amount of penalty to lift and drag [14]. Figure 3.17 shows the bending moment versus the tip pitch angle as well as the optimum tip pitch angle for the NREL Phase VI rotor. Figure 3.18 shows the angle of attack versus the radial location at various tip pitch angles. As can be seen, the angles of attack for the optimum tip pitch angle of 86 are close to zero especially for the outboard radial locations that contribute largely to the bending moment due to the high lever arm. Figure 3.17: Case 3: Bending Moment vs. Blade Tip Pitch Angle for the NREL Phase VI 41

58 Figure 3.18: Case 3: Angle of Attack vs. Radial Location at various Tip Pitch Angles for the NREL Phase VI Using the optimum pitch angle, the wind turbine was run in XTURB in a parked condition, that is, at zero RPM during the icing event. After the icing event was completed, the wind turbine was set back to its nominal tip pitch angle of 3, and BEMT was run again at a wind speed of 7 m/s at 72 RPM. The performance of the NREL Phase VI run under Case 3 is shown in Table 3.5. As seen, there was only a 2.1% decrease in rotor thrust and more importantly, a 6.5% loss in power after the icing event was complete. Table 3.5: Case 3: Performance degradation of the NREL Phase VI Rotor at V W ind = 7 m/s, RPM = 72 and Tip Pitch Angle = 86. NREL Phase VI Thrust [N] Power [W] Nominal Case Percent Loss 2.1% 6.5 % Figures 3.19 to 3.21 show the angle of attack, lift coefficient, and drag coefficient versus the radial location respectively. The angle of attack does not change when compared to the nominal case and because of this, the lift coefficient does not decrease significantly from the nominal case either. However, drag does increase especially at the outboard sections. 42

59 Figure 3.19: Case 3: Angle of Attack vs. Radial Location of the Clean and Iced NREL Phase VI Figure 3.20: Case 3: Lift Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI 43

60 Figure 3.21: Case 3: Drag Coefficient vs. Radial Location of the Clean and Iced NREL Phase VI Once more, the decrease in lift and the increase in drag reduces both the thrust and power production of the NREL Phase VI rotor when compared to the nominal case. Both power versus radial location and thrust versus radial location are shown in Figures 3.22 and 3.23, respectively. It can be concluded that parking the wind turbine during this particular icing event is a more practical way to run the wind turbine when compared to Case 1. Figure 3.22: Case 3: Power vs. Radial Location of the Clean and Iced NREL Phase VI 44

61 Figure 3.23: Case 3: Thrust vs. Radial Location of the Clean and Iced NREL Phase VI 3.6 Comparison Between Cases 1-3 Cases 1-3 provided different methods of operating the wind turbine during the icing event shown in Table 3.2. Case 1 concerned running the wind turbine normally during the icing event. Case 2 was running the wind turbine at a decreased RPM and higher tip pitch angle when compared to the baseline case. Case 3 was parking the wind turbine with a high tip pitch angle relative to the baseline case during the icing event. Table 3.6 shows the thrust and power comparisons of all three cases that were run. Table 3.6: Thrust and Power Comparison of Case 1-3 NREL Phase VI Nominal Case 1 Case 2 Case 3 Thrust [N] Power [W] In the following section, three different radial locations will be analyzed for the NREL Phase VI rotor as shown in Table 3.7. Note that the more interesting radial locations for this wind turbine were located outboard as there was more ice accreted than at the inboard sections. These ice shapes are seen in Figure

62 Table 3.7: Radial Locations Analyzed for the NREL Phase VI Rotor, Nominal Case Radial Section A B C r/r Section Radius [m] Airfoil S809 S809 S809 Chord, c r [m] (Iced) Angle of Attack, α [deg] Relative Velocity, V rel [m/s] Figure 3.24: Clean and Iced Airfoil Shapes for All Three Radial Locations Using the method described earlier by Lee and Brag [14], ice shape parameters were calculated on the ice shapes shown in Figure 3.24 in order to determine the updated lift and drag curves. Figure 3.25 shows the updated lift curves for the NREL Phase VI rotor for all three cases run. As shown, there is much less lift for Case 1 at the outboard sections followed by Case 2. The least amount of change from the nominal lift curve is Case 3, where the wind turbine was parked at high tip pitch angle relative to the nominal case. Figure 3.25: Clean and Iced Airfoil Shapes for All Three Radial Locations The same trends can be observed for the drag polars as well shown in Figure Case 1 has the largest increase in drag followed by Case 2 and then by Case 3. This makes sense, since the largest 46

63 ice shapes relative to the airfoil chord occur in Case 1 followed by Case 2 and then by Case 3. Figure 3.26: Clean and Iced Airfoil Shapes for All Three Radial Locations The loss in power in Case 1 compared to Case 2 and Case 3 shows that running the NREL Phase VI rotor normally during an icing event is not efficient. Case 3 accretes the least amount of ice, which is attributed to the lowest velocities that an airfoil section sees in the parked condition. Although the difference in power loss between Case 2 and Case 3 is negligible, it still cannot be said definitively that Case 2 should be chosen instead of Case 3. However, this does show that there may be a more cost effective way of running a wind turbine during an icing event and more analysis is required. 3.7 Validation of TIOCS Reid et al. [28] ran a numerical performance degradation analysis of the NREL Phase VI operating under icing conditions using FENSAP-ICE. The airflow simulations were computed with the FENSAP module, which solves the Reynolds-Averaged Navier-Stokes (RANS). ICE3D has the capability of simulating all icing regimes, from glaze to rime [29]. Water run-back is computed based on surface water thermodynamics equations [30]. The icing event conditions are shown in Table 3.8. Table 3.8: Icing Event Conditions Case I-10 Case I-20 Velocity, U inf 7 7 Static air temperature, T s -3 C -3 C Droplet diameter, MVD 20 µm 20 µm Liquid water content, LWC 0.5 g/m g/m 3 Icing time, t 10 min 20 min The clean and iced conditions presented in Table 3.8 were run in TIOCS and were compared to Reid et al. [28] as well as experimental results collected in the NASA Ames 80x120 ft wind tunnel [31]. For the clean blade, Figure 3.27 shows the measured torque as a function of the wind speed 47

64 for the clean NREL Phase VI rotor for NASA data, FENSAP-ICE, and TIOCS. As shown, the BEMT solver run in XTURB (TIOCS) stays within the experimental data however it under-predicts the torque for wind speeds less than 17 m/s when compared to FENSAP-ICE. This is expected as FENSAP-ICE resolves the three-dimensional aerodynamic effects, whereas XTURB is run using Prandtl s root and tip loss factor. Figure 3.27: Clean: Torque [Nm] versus Approach Wind Speed [m/s] for the simulated NREL Phase VI rotor [28] [31]. Figure 3.28 shows predicted torque versus wind speed from both FENSAP-ICE and TIOCS for Case I-10 and Case I-20. TIOCS predicts a lower amount of torque due to ice than FENSAP-ICE. This is to be expected for wind speeds less than 17 m/s since the clean case torque versus wind speed was also lower in this region. Although TIOCS is lower than FENSAP-ICE, the trends match quite well. 48

65 Figure 3.28: Iced: Torque [Nm] versus Approach Wind Speed [m/s] for the simulated NREL Phase VI rotor Some further investigation involves Figure 3.29 that shows the percent power loss versus wind speed from predictions from FENSAP-ICE and TIOCS. TIOCS predicts a much greater power loss for both Case I-10 and for Case I-20. Figure 3.29: Iced: Torque Percent Power Loss versus Approach Wind Speed [m/s] for the simulated NREL Phase VI rotor 49

66 Chapter 4 NREL 5 MW Results 4.1 Atmospheric Icing Parameters The atmospheric icing conditions for LEWICE can be seen in Table 4.1. These icing parameters are taken from Homala et al. [4] for validation purposes of TIOCS. Table 4.1: Icing Simulation Conditions at V wind = 10m/s Icing Event Time [s] 3600 Droplet Size, MVD [µm] 20 Liquid Water Content, LWC [g m 3 ] 0.22 Air Temperature [ C] -10 Atmospheric Pressure [N m 2 ] NREL 5MW Wind Turbine Parameters The NREL 5MW is a three-bladed pitch-controlled wind turbine. It is rated at 5.0 MW of power and 0.7 MN of thrust at a wind speed of 11.4 m/s at SSL. The rotor parameters that were run in TIOCS are presented in Table 4.2. The chord distribution is shown in Figure 4.1, the twist distribution in Figure 4.2, the nominal power versus radial location in Figure 4.3, and the nominal thrust is shown in Figure 4.4. The chord distribution as well as airfoils were taken from Jonkman et al. [32], see Appendix A.2 for more information on the NREL 5MW rotor. Table 4.2: NREL 5MW Wind Turbine Parameters Blade Number 3 Blade Radius [m] 63.0 Rotor RPM Blade Tip Pitch [deg] 0 Wind Speed [m/s] 10 Nominal Power [MW] 3.69 Nominal Thrust [MN] Power Coefficient Thrust Coefficient

67 Figure 4.1: Chord Distribution of the NREL 5MW Wind Turbine Blade Figure 4.2: Twist Distribution of the NREL 5MW Wind Turbine Blade 51

68 Figure 4.3: Nominal Power vs r/r for the NREL 5MW Figure 4.4: Nominal Thrust vs r/r for the NREL 5MW 4.2 Case 1: Baseline Operating Conditions during Icing Event The NREL 5MW wind turbine was run under normal operating conditions from Table 4.2 during a 60 minute icing event as described in Table 4.1. Table 4.3 presents an analysis of the performance degradation of the NREL 5MW at a wind speed of 10 m/s. The thrust extracted under the nominal operation of the rotor is 0.60 MN while under the icing condition it is 0.58 MN; a decrease of 3.33%. The power extracted under the nominal operation of the rotor is

69 MW, while under the icing condition it is 3.31 MW; a loss of 10.5%. Table 4.3: Case 1: Performance degradation of the NREL 5MW Rotor at V W ind = 10 m/s, RPM = and Tip Pitch Angle = 0. NREL 5MW Thrust [MN] Power [MW] Nominal Case Percent Loss 3.33% 10.5% Figure 4.5 shows the angle of attack along the blade span after the icing event has taken place. The scaling of the y-axis has been fitted so that the outboard angles of attack can be seen with ease. There is a slight increase in the angle of attack after the icing event has taken place. This increase of angle of attack has a negligible effect on aerodynamic properties when compared to the new iced airfoil shapes. Figure 4.6 shows the local lift coefficient along the span of the blade. There is a small decrease in the lift coefficient after the icing event when compared to the clean case that contributes to the total power loss. Although there was a slight change in the lift coefficient, the same cannot be said for the drag coefficient shown in Figure 4.7. The drag coefficient shows a large increase especially for r/r > 0.5 that greatly contributes to the total loss of power. Figure 4.5: Case 1: Angle of Attack vs. Radial Location of the Clean and Iced NREL 5MW 53

70 Figure 4.6: Case 1: Lift Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Figure 4.7: Case 1: Drag Coefficient vs. Radial Location of the Clean and Iced NREL 5MW A combination of a decrease in the local lift coefficients and an increase in the local drag coefficients along the span of the blade decreases both the thrust and power produced by the NREL 5MW. Figures 4.8 and 4.9 show the power and thrust versus the radial location. 54

71 Figure 4.8: Case 1: Power per unit span vs. Radial Location of the Clean and Iced NREL 5MW Figure 4.9: Case 1: Thrust per unit span vs. Radial Location of the Clean and Iced NREL 5MW 4.3 Case 2: Wind Turbine Operation at a Higher Tip Pitch Angle and Decreased RPM The NREL 5MW rotor was run at an increased tip pitch angle as well as a reduced RPM setting. It was found that running the rotor at an RPM of 6 and a tip pitch angle of 17 yielded the best results in regards to power production post icing. Table 4.4 shows the performance degradation of this scenario. The rotor thrust under the baseline operation of the rotor is MN, while under 55

72 the icing condition it is MN; a decrease of 1.67%. The power extracted under the nominal operation of the rotor is 3.69 MW, while under the icing condition it is 3.47 MW; a loss of 5.96%. Table 4.4: Case 2: Performance degradation of the NREL 5MW Rotor at V W ind = 10 m/s, RPM = 6 and Tip Pitch Angle = 17. NREL 5MW Thrust [MN] Power [MW] Nominal Case Percent Loss 1.67% 5.96% Figures 4.10 to 4.12 show the angle of attack, lift coefficient, and drag coefficient versus the radial location, respectively. As shown, the angle of attack does not change significantly when compared to the baseline case and because of this, the lift coefficient does not decrease significantly from the baseline case either. However, drag does increase especially in the outboard sections due to the newly formed ice shapes. This increase in drag at the outboard section of the blade affects the power produced and thrust of the wind turbine. This is shown in Figures 4.13 and Case 2 is a better method than Case 1 of running a wind turbine during an icing event. Figure 4.10: Case 2: Angle of Attack vs. Radial Location of the Clean and Iced NREL 5MW 56

73 Figure 4.11: Case 2: Lift Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Figure 4.12: Case 2: Drag Coefficient vs. Radial Location of the Clean and Iced NREL 5MW 57

74 Figure 4.13: Case 2: Power vs. Radial Location of the Clean and Iced NREL 5MW Figure 4.14: Case 2: Thrust vs. Radial Location of the Clean and Iced NREL 5MW 4.4 Case 3: Parking the Wind Turbine with High Tip Pitch Angle The final case explored was parking the wind turbine with the highest tip pitch angle that produced the least amount of bending moment in which the angle of attack distribution remained relatively small. Figure 4.15 shows the bending moment as a function of the blade tip pitch angle. As shown, the tip pitch angle that produces the minimum bending moment is 87. The angle of attack distribution at this tip pitch angle is presented in Figure The angle of attack at 58

75 r/r < 0.4 is less than what LEWICE is validated for, however, this is negligible since the majority of power produced is at r/r > 0.5. Figure 4.15: Case 3: Bending Moment vs. Blade Tip Pitch Angle for the NREL 5MW Figure 4.16: Case 3: Angle of Attack vs. Radial Location at various Tip Pitch Angles for the NREL 5MW Table 4.5 shows the performance degradation of parking the NREL 5MW rotor at a tip pitch angle of 87. The rotor thrust under the baseline operation of the rotor is MN, while under the icing condition it is MN; a decrease of 0.67%. The power extracted under the baseline operation of the rotor is 3.69 MW, while under the icing condition it is 3.60 MW; a loss of 2.44%. 59

76 Table 4.5: Case 3: Performance degradation of the NREL 5MW Rotor at V W ind = 10 m/s, RPM = 6 and Tip Pitch Angle = 87. NREL 5MW Thrust [MN] Power [MW] Nominal Case Percent Loss 0.67% 2.44% Figures 4.17 to 4.19 show the angle of attack, lift coefficient, and drag coefficient versus the radial location, respectively. As shown, the angle of attack does not change significantly when compared to the baseline case and because of this, the lift and drag coefficients does not change significantly from the baseline case either. Figure 4.17: Case 3: Angle of Attack vs. Radial Location of the Clean and Iced NREL 5MW 60

77 Figure 4.18: Case 3: Lift Coefficient vs. Radial Location of the Clean and Iced NREL 5MW Figure 4.19: Case 3: Drag Coefficient vs. Radial Location of the Clean and Iced NREL 5MW The power and thrust extracted is shown in Figures 4.20 and Note that the power and thrust loss seems to occur at r/r < 0.4 which was exactly where the angles of attack were not validated in LEWICE. Case 3 is a better method than Case 1 of running a wind turbine during an icing event. 61

78 Figure 4.20: Case 3: Power vs. Radial Location of the Clean and Iced NREL 5MW Figure 4.21: Case 3: Thrust vs. Radial Location of the Clean and Iced NREL 5MW 4.5 Comparison Between Cases 1-3 Cases 1-3 provided different methods of operating the wind turbine during the icing event shown in Table 4.1. Case 1 concerned running the wind turbine normally during the icing event. Case 2 was running the wind turbine at a decreased RPM and higher tip pitch angle when compared to the baseline case. Case 3 was parking the wind turbine with a high tip pitch angle relative to the baseline case during the icing event. Table 4.6 shows the thrust and power comparisons of all 62

79 three cases that were run. Table 4.6: Thrust and Power Comparison of Case 1-3 NREL 5MW Nominal Case 1 Case 2 Case 3 Thrust [MN] Power [MW] In the following section, three different radial locations will be analyzed for the NREL 5MW rotor as shown in Table 4.7. Note that the more interesting radial locations for this wind turbine were located outboard as there was more ice accreted than at the inboard sections. These ice shapes are seen in Figure Table 4.7: Radial Locations Analyzed for the NREL 5MW Rotor, Nominal Case Radial Section A B C r/r Section Radius [m] Airfoil NACA64 NACA64 NACA64 Chord, c r [m] Angle of Attack, α [deg] Relative Velocity, V rel [m/s] Figure 4.22: Clean and Iced Airfoil Shapes for All Three Radial Locations Using the method described earlier by Lee and Brag [14], ice shape parameters were calculated on the ice shapes shown in Figure 4.22 in order to determine the updated lift and drag curves. Figure 4.23 shows the updated lift curves for the NREL 5MW rotor for all three cases run. As shown, there is much less lift for Case 1 at the outboard sections followed by Case 2. The least amount of change from the nominal lift curve is Case 3, where the wind turbine was parked at high tip pitch angle relative to the nominal case. 63

80 Figure 4.23: Clean and Iced Airfoil Shapes for All Three Radial Locations The same trends can be observed for the drag polars as well shown in Figure Case 1 has the largest increase in drag followed by Case 2 and then by Case 3. This makes sense, since the largest ice shapes relative to the airfoil chord occur in Case 1 followed by Case 2 and then by Case 3. Figure 4.24: Clean and Iced Airfoil Shapes for All Three Radial Locations 4.6 Validation of TIOCS Homola et al. [4] iced the NREL 5MW rotor under icing conditions shown in Table 4.8 which were also the same conditions that were run for Cases 1-3. Homola et al. used FENSAP-ICE to accrete ice and determined aerodynamic properties on 5 different radial sections along the span of the blade instead of the 21 that were run in TIOCS due to computational constraints. They then used the iced aerodynamic properties to run BEMT on those iced sections. Table 4.8: Icing Simulation Conditions Icing Event Time [sec] 3600 Droplet Size, MVD [µm] 20 Liquid Water Content, LWC [g m 3 ] 0.22 Air Temperature [ C] -10 Atmospheric Pressure [N m 2 ]

81 The 5 radial sections that were run by Homala et al. [4] were also run in TIOCS. These radial locations are shown in Table 4.9. Table 4.9: Radial Locations Analyzed for the NREL 5MW Rotor, Homola et al. [4] Radial Section A B C D E r/r Section Radius [m] Airfoil DU40 DU25 DU21 NACA64 NACA64 Chord, c r [m] The 5 radial sections were run in TIOCS and were then compared to Homola et al. [4]. Figure 4.25 shows the power coefficient as a function of tip speed ratio of the clean and iced cases produced by both TIOCS and Homola et al. [4]. As shown, TIOCS underpredicted the baseline power coefficient when compared to Homola et al., however, the trends matched fairly well. This may be caused by several factors including different airfoil polar files, the method of including three-dimensional effects, etc. It is interesting that the iced cases not only match trends, but also matched power coefficient values. It seems that TIOCS has matched a more elegant method of determining airfoil properties using FENSAP-ICE. More investigation is necessary though since BEMT used with all of its assumptions. Figure 4.25: A Comparison of Power Coefficient versus Tip Speed Ratio between Homola et al. [4] and TIOCS. 65

82 Chapter 5 PSU 2.5MW Results 5.1 Atmospheric Icing Parameters The atmospheric icing conditions for LEWICE can be seen in Table 5.1. The icing event time chosen was reduced to 45 minutes when compared to the NREL 5MW because of the smaller wind turbine blade. Also, the icing event conditions used were taken from Reid et al. [28]. Table 5.1: Icing Simulation Conditions Icing Event Time [sec] 2700 Droplet Size, MVD [µm] 20 Liquid Water Content, LWC [g m 3 ] 0.50 Air Temperature [ C] -3 Atmospheric Pressure [N m 2 ] PSU 2.5MW Wind Turbine Parameters The PSU 2.5MW is a three-bladed pitch-controlled wind turbine. It is rated at 2.5 MW of power and 0.7 MN of thrust at a wind speed of 12.0 m/s at SSL. The rotor parameters that were run in TIOCS are presented in Table 5.2. The chord distribution is shown in Figure 5.1, the twist distribution in Figure 5.2. See Appendix A.3 for more information on the PSU 2.5MW rotor. Table 5.2: PSU 2.5MW Wind Turbine Parameters Blade Number 3 Blade Radius [m] 45.0 Rotor RPM Blade Tip Pitch [deg] 0 Wind Speed [m/s] 12 Power [MW] 2.64 Thrust [MN] Power Coefficient Thrust Coefficient

83 Figure 5.1: Chord Distribution of the PSU 2.5MW Wind Turbine Blade Figure 5.2: Twist Distribution of the PSU 2.5MW Wind Turbine Blade The baseline power along the blade span is shown in Figure 5.3, and the baseline thrust is shown in Figure 5.4. The majority of power production for the PSU 2.5MW blade is at the outboard sections, that is r/r >

84 Figure 5.3: Nominal Power vs r/r for the PSU 2.5MW Figure 5.4: Nominal Thrust vs r/r for the PSU 2.5MW 5.2 Case 1: Baseline Operating Conditions during Icing Event The PSU 2.5MW wind turbine was run under normal operating conditions from Table 5.2 during a 45 minute icing event as described in Table 5.1. Table 5.3 presents an analysis of the performance degradation of the PSU 2.5MW at a wind speed of 12 m/s. The rotor thrust under the baseline operation of the rotor is MN while under icing condition it is MN; a decrease of 18.65%. The power extracted under the nominal operation of the rotor is 2.64 MW 68

85 while under icing condition it is 1.69 MW; a loss of 36.0%. Table 5.3: Case 1: Performance degradation of the PSU 2.5MW Rotor at V W ind = 12 m/s, RPM = and Tip Pitch Angle = 0. PSU 2.5MW Thrust [MN] Power [MW] Nominal Case Percent Loss 18.65% 36.0% Figure 5.5 shows the angle of attack along the blade span after the icing event has taken place. The scaling of the y-axis has been fitted so that the outboard angles of attack can be seen with ease. There is a slight increase in the angle of attack after the icing event has taken place. This increase of angle of attack has a negligible effect on aerodynamic properties when compared to the new iced airfoil shapes. Figure 5.6 shows the local lift coefficient along the span of the blade. The decrease in lift at the inboard sections is attributed to a correction routine implemented in TIOCS. This lift decrease has a negligible effect on the total power. There is a large decrease in the lift coefficient after the icing event at the outboard sections when compared to the clean case that contributes to the total power loss. The drag coefficient shown in Figure 5.7 shows a large increase especially for r/r > 0.6 that greatly contributes to the total loss of power. Figure 5.5: Case 1: Angle of Attack vs. Radial Location of the Clean and Iced PSU 2.5MW 69

86 Figure 5.6: Case 1: Lift Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Figure 5.7: Case 1: Drag Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW A combination of a decrease in the local lift coefficients and an increase in the local drag coefficients along the span of the blade decreases both the thrust and power produced by the PSU 2.5MW. Figures 5.8 and 5.9 show the power and thrust versus the radial location. 70

87 Figure 5.8: Case 1: Power per unit span vs. Radial Location of the Clean and Iced PSU 2.5MW Figure 5.9: Case 1: Thrust per unit span vs. Radial Location of the Clean and Iced PSU 2.5MW 5.3 Case 2: Wind Turbine Operation at a Higher Tip Pitch Angle and Decreased RPM The PSU 2.5MW rotor was run at an increased tip pitch angle as well as a reduced RPM setting. It was found that running the rotor at an RPM of 6.8 and a tip pitch angle of 20 yielded the best results in regards to power production post icing. Table 5.4 shows the performance degradation of this scenario. The rotor thrust under the baseline operation of the rotor is MN, while under 71

88 the icing condition it is MN; a decrease of 18.1%. The power extracted under the baseline operation of the rotor is 2.64 MW, while under the icing condition it is 2.00 MW; a loss of 24.2%. Table 5.4: Case 2: Performance degradation of the PSU 2.5MW Rotor at V W ind = 12 m/s, RPM = 6.8 and Tip Pitch Angle = 20. PSU 2.5MW Thrust [MN] Power [MW] Nominal Case Percent Loss 18.1% 24.2 % Figures 5.10 to 5.12 show the angle of attack, lift coefficient, and drag coefficient versus the radial location, respectively. As shown, the angle of attack shows an increase when compared to the baseline case, however the lift coefficient decreases from the baseline case to the newly accreted ice. Drag also shows an increase especially at the outboard sections. Figure 5.10: Case 2: Angle of Attack vs. Radial Location of the Clean and Iced PSU 2.5MW 72

89 Figure 5.11: Case 2: Lift Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Figure 5.12: Case 2: Drag Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Figures 5.13 and 5.14 show the power and thrust after the icing event has taken place. When compared to Case 1, Case 2 shows a less loss in both power and thrust. This is attributed to less ice growth severity and will be discussed later. 73

90 Figure 5.13: Case 2: Power vs. Radial Location of the Clean and Iced PSU 2.5MW Figure 5.14: Case 2: Thrust vs. Radial Location of the Clean and Iced PSU 2.5MW 5.4 Case 3: Parking the Wind Turbine with High Tip Pitch Angle The final case explored was parking the wind turbine with the highest tip pitch angle that produced the least amount of bending moment in which the angle of attack distribution remained relatively small. Figure 5.15 shows the bending moment as a function of the blade tip pitch angle. As shown, the tip pitch angle that produces the minimum bending moment is 88. The angle of attack distribution at this tip pitch angle is presented in Figure The angle of attack at 74

91 r/r < 0.5 is less than what LEWICE is validated for, however, this is negligible since the majority of power produced is at r/r > 0.6. Figure 5.15: Case 3: Bending Moment vs. Blade Tip Pitch Angle for the PSU 2.5MW Figure 5.16: Case 3: Angle of Attack vs. Radial Location at various Tip Pitch Angles for the PSU 2.5MW Table 5.5 shows the performance degradation of parking the PSU 2.5MW rotor at a tip pitch angle of 88. The rotor thrust under the baseline operation of the rotor is MN, while under the icing condition it is MN; a decrease of 11.25%. The power extracted under the baseline operation of the rotor is 2.64 MW, while under the icing condition it is 2.26 MW; a loss of 14.4%. 75

92 Table 5.5: Case 3: Performance degradation of the PSU 2.5MW Rotor at V W ind = 12 m/s, RPM = and Tip Pitch Angle = 0. PSU 2.5MW Thrust [MN] Power [MW] Nominal Case Percent Loss 11.25% 14.4 % Figures 5.17 to 5.19 show the angle of attack, lift coefficient, and drag coefficient versus the radial location, respectively. As shown, the angle of attack does not change significantly at the outboard sections when compared to the baseline case and because of this, the lift and drag coefficients do not change significantly from the baseline case either at the outboard sections. Figure 5.17: Case 3: Angle of Attack vs. Radial Location of the Clean and Iced PSU 2.5MW 76

93 Figure 5.18: Case 3: Lift Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Figure 5.19: Case 3: Drag Coefficient vs. Radial Location of the Clean and Iced PSU 2.5MW Figures 5.20 and 5.21 show the power and thrust after the icing event has taken place. When compared to Case 1 and Case 2, Case 3 shows a less loss in both power and thrust. 77

94 Figure 5.20: Case 3: Power vs. Radial Location of the Clean and Iced PSU 2.5MW Figure 5.21: Case 3: Thrust vs. Radial Location of the Clean and Iced PSU 2.5MW 5.5 Comparison Between Cases 1-3 Cases 1-3 provided different methods of operating the wind turbine during the icing event shown in Table 5.1. Case 1 concerned running the wind turbine normally during the icing event. Case 2 was running the wind turbine at a decreased RPM and higher tip pitch angle when compared to the baseline case. Case 3 was parking the wind turbine with a high tip pitch angle relative to the baseline case during the icing event. Table 5.6 shows the thrust and power comparisons of all 78

95 three cases that were run. Table 5.6: Thrust and Power Comparison of Case 1-3 PSU 2.5MW Nominal Case 1 Case 2 Case 3 Thrust [MN] Power [MW] In the following section, three different radial locations will be analyzed for the PSU 2.5MW rotor as shown in Table 5.7. Note that the more interesting radial locations for this wind turbine were located outboard as there was more ice accreted than at the inboard sections. These ice shapes are seen in Figure Table 5.7: Radial Locations Analyzed for the PSU 2.5MW Rotor, Nominal Case Radial Section A B C r/r Section Radius [m] Airfoil 93W210DUT 95W180DUT 95W180DUT Chord, c r [m] Angle of Attack, α [deg] Relative Velocity, V rel [m/s] Figure 5.22: Clean and Iced Airfoil Shapes for All Three Radial Locations Using the method described earlier by Lee and Brag [14], ice shape parameters were calculated on the ice shapes shown in Figure 5.22 in order to determine the updated lift and drag curves. Figure 5.23 shows the updated lift curves for the PSU 2.5MW rotor for all three cases run. As shown, there is much less lift for Case 1 at the outboard sections followed by Case 2. The least amount of change from the nominal lift curve is Case 3, where the wind turbine was parked at high tip pitch angle relative to the nominal case. 79

96 Figure 5.23: Clean and Iced Airfoil Shapes for All Three Radial Locations The same trends can be observed for the drag polars as well shown in Figure Case 1 has the largest increase in drag followed by Case 2 and then by Case 3. This makes sense, since the largest ice shapes relative to the airfoil chord occur in Case 1 followed by Case 2 and then by Case 3. Figure 5.24: Clean and Iced Airfoil Shapes for All Three Radial Locations 80

97 Chapter 6 Summary and Conclusions The purpose of this thesis was to develop an engineering tool to help understand the altered aerodynamic performance caused by atmospheric surface icing on a wind turbine blade. The Turbine Icing Operation Control System (TIOCS) was developed that couples a blade-element momentum theory code (XTURB), an ice accretion code (LEWICE), as well as an empirical methodology to predict aerodynamic properties of an iced airfoil shape. TIOCS ices a user-specified number of radial stations along a wind turbine blade span, updates the aerodynamic properties of the new iced shape, and finally runs BEMT to analyze the performance degradation of the iced wind turbine blade. Three different wind turbines were analyzed in TIOCS: the NREL Phase VI rotor, the NREL 5MW rotor, and the PSU 2.5MW rotor. Three different methods of operating each wind turbine during an icing event were investigated. The first operating condition was that of the baseline case, that is, running the wind turbine normally during the icing event. The second operating condition concerned running the wind turbine during the icing event at a decreased RPM in order to decrease the relative velocities along the blade span, and running at an increased tip pitch angle in order to accrete ice along the mean camber line of the airfoil section. The third operating condition was parking the wind turbine blade during the icing event at an extremely high tip pitch angle to decrease the relative velocities along the blade span. It was found that running the wind turbine normally during an icing event was not the best conditions. Instead, running the wind turbine at a decreased RPM and increased tip pitch angle or either parking the wind turbine at a very high tip pitch angle accreted the least amount of ice. This was found to have minimal effect on the aerodynamic properties of the blade and therefore affecting the wind turbine performance by the least amount. It cannot definitively be stated whether Case 2 (high tip pitch angle and decreased RPM) or Case 3 (parking the wind turbine at very high tip pitch angle) was the better set of operating conditions during an icing event. However, it can be stated that there seems to be a more cost-effective set of operating conditions to run during an icing event and that leads to a decreased loss in Annual Energy Production (AEP). A further and more complete investigation of icing of wind turbine blades is needed. Future work should include studying the ice accretion on the blade further including ice mass, centrifugal and gravitational effects, rotor imbalance effects, and deicing techniques. LEWICE3D or TURBICE should be incorporated into TIOCS in order to incorporate three-dimensional effects on ice shapes. Also, an empirical scheme was implemented in TIOCS that used experimental data 81

98 in order to update iced airfoil performance. Although this method was very quick to run, perhaps a better method in predicting iced aerodynamic data is needed. BEMT was used in this thesis because it is computationally inexpensive and takes seconds to run, however, BEMT does not fully capture the fluid dynamics of the blade. Instead, the Helicodal Vortex Wake Method (HVM) or possibly even hybrid computational fluid dynamics methods should be studied. Although the above suggestions will increase TIOCS run-time, they can be used to help in the validation of TIOCS beyond its current state. Some recommendations for the actual TIOCS software are: a graphical user interface (GUI) should be implemented for easier data manipulation by the user. TIOCS should consider using parallel processing to increase run-times since only one instance of LEWICE can be run in the current version of TIOCS. Although MATLAB was the language TIOCS was written in, it is not easily distributable. Perhaps using another programming language is necessary. Overall, TIOCS has been a useful tool in understanding the altered aerodynamic performance caused by atmospheric surface icing on a wind turbine blade. It has shown the effects of chord length, relative velocities, and angle of attack as well as liquid water content, median volumetric diameter, and temperature on ice growth. TIOCS has also been helpful in understanding the detrimental effects that ice has on the aerodynamic properties on an airfoil shape, which lead to a decrease in rotor thrust and a loss in power on a wind turbine blade. Finally, TIOCS has shown that parking a wind turbine during an icing event may not be the optimum method for cost-effective operation. More research is necessary, however, TIOCS is heading in the right direction and can potentially be a useful engineering tool in the wind energy industry. 82

99 References [1] L. Fried, S. Sawyer, S. Shukla, and L. Qiao, Global wind report, tech. rep., Global Wind Energy Council, [2] N. Dalili, A. Edrisy, and R. Carriveau, A review of surface engineering issues critical to wind turbine performance, Renewable and Sustainable Energy Reviews, vol. 13, pp , [3] L. Makkonen, T. Laakso, and M. Marjaniemi, Modelling and prevention of ice accretion on wind turbines, Wind Engineering, vol. Vol. 25, no. No. 1, p. pp. 3 21, [4] M. C. Homola, M. S. Virk, P. J. Nicklasson, and P. A. Sundsbø, Performance losses due to ice accretion for a 5 mw wind turbine, Wind Energy, [5] P. Giguère and M. Selig, Design of a tapered and twisted blade for the nrel combined experiment rotor, tech. rep., National Renewable Energy Laboratory, [6] D. Somers, Design and experimental results for the s809 airfoil, tech. rep., National Renewable Energy Laboratory, Golden,CO, [7] O. Byrkjedal and K. Vindteknikk, Estimating wind power production loss due to icing, in Proceedings of the IWAIS XIII (. Andermatt, ed.), [8] P. K. Jha, D. Brillembourg, and S. Schmitz, Wind turbines under atmospheric icing conditions - ice accretion modeling, aerodynamics, and control strategies for mitigating performance degradation, in AIAA , [9] M. S. Brower, M. W. Tennis, E. W. Denzier, and M. M. Kaplan, Powering the Midwest: Renewable Electricity for the Economy and the Environment. Cambridge, MA: Union of Concerned Scientists, [10] A. J. Cavallo, S. M. Hock, and D. R. Smith, Renewable Energy: Sources for Fuels and Electricity, ch. Wind Energy: Technology and Economics, p Island Press, [11] Y. Han, J. Palacios, and S. Schmitz, Scaled ice accretion experiments on a rotating wind turbine blade, Journal of Wind Engineering and Industrial Aerodynamics, vol. 109, pp , [12] S. Schmitz, XTurb-PSU. The Pennsylvania State University. [13] W. B. Wright, User Manual for the NASA Glenn Ice Accretion Code LEWICE. NASA. 83

100 [14] S. Lee and M. B. Bragg, Investigation of factors affecting iced-airfoil aerodynamics, Journal of Aircraft, vol. Vol. 40, May June [15] J. J. Chattot, Design and analysis of wind turbines using helicoidal vortex model, Computational Fluid Dynamics Journal, vol. 11, pp , April [16] M. O. Hansen, Aerodynamics of Wind Turbines (2nd Edition). Earthscan, [17] J. F. Manwell, J. G. McGowan, and A. L. Rogers, Wind energy explained: theory, design and application. Wiley, [18] H. Glauert, Airplane propellers, in Aerodynamic Theory, pp , Springer Berlin Heidelberg, [19] P. Moriarty and A. Hansen, Aerodyn theory manual, tech. rep., National Renewable Energy Laboratory, [20] T. Burton, J. D. Sharpe, and N. E. Bossanyi, Handbook of Wind Energy. John Wiley and Sons, [21] J. Dowler, A solution based stall delay model for horizontal axis wind turbines, Master s thesis, The Pennsylvania State University, [22] N. P. D. R. W. Gent and J. T. Cansdale, Aircraft icing, Philosophical Transactions: Mathematical, Physical and Engineering Sciences, vol. 358, pp , November [23] T. T. Lankford, Aviation Weather Handbook. New York: McGraw-Hill, [24] N. Czernkovich, Understanding in-flight icing. [25] H. S. Kim and M. B. Bragg, Effects of leading-edge ice accretion geometry on airfoil performance, (Reno, NV), [26] E. Loth and M. B. Bragg, Effects of large-droplet ice accretion on airfoil and control, tech. rep., U.S. Department of Transportation, Washington, DC, [27] M. C. Homola, T. Wallenius, L. Makkonen, P. J. Nicklasson, and P. A. Sundsbo, The relationship between chord length and rime icing on wind turbines, Wind Energy, vol. 13, no. 7, pp , [28] T. Reid, G. Baruzzi, I. Ozcer, D. Switchenko, and W. G. Habashi, Fensap-ice simulation of icing on wind turbine blades, part 1: Performance degradation, No. 0750, American Institute of Aeronautics and Astronautics, Inc., [29] H. Beaugendre, F. Morency, and W. G. Habashi, Fensap-ice s three-dimensional in-flight ice accretion module: Ice3d, Journal of Aircraft,

101 [30] B. L. Messinger, Equilibrium temperature of an unheated icing surface as a function of airspeed, Journal of Aeronautical Sciences, [31] N. N. Sorensen, J. A. Michelsen, and S. Schreck, Navier stokes predictions of the nrel phase vi rotor in the nasa ames 80 ft x 120 ft wind tunnel, Wind Energy, vol. 5, no. 2-3, pp , [32] J. Jonkman, S. Butterfield, W. Musial, and G. Scott, Definition of a 5-mw reference wind turbine for offshore system development, tech. rep., National Renewable Energy Laboratory, February [33] M. Drela and H. Youngren, XFOIL 6.9 User Primer. 85

102 Appendix A Wind Turbine Configurations A.1 NREL Phase VI The NREL Phase Vi rotor parameters are shown in Table A.1. Table A.1: NREL Phase VI Wind Turbine Parameters Blade Number 2 Blade Radius [m] 5.03 Rotor RPM 72 Blade Tip Pitch [deg] 3 Wind Speed [m/s] 7 Power [W] 5692 Thrust [N] 1120 Power Coefficient Thrust Coefficient The chord and twist distribution for the NREL Phase VI rotor is shown Figure A.1. Figure A.1: Chord and Twist Distribution for the NREL Phase VI Wind Turbine Table A.2: NREL Phase VI Airfoil Locations r/r Airfoil 0.25 S809 86

103 Figure A.2: Lift and Drag Coefficient vs Angle of Attack for the S809 Airfoil 87

104 A.2 NREL 5 MW The NREL 5 MW rotor parameters are shown in Table A.3. Table A.3: NREL 5W Wind Turbine Parameters Blade Number 3 Blade Radius [m] 63.0 Rotor RPM Blade Tip Pitch [deg] 0 Rated Wind Speed [m/s] 10 Nominal Power [MW] 3.7 Nominal Thrust [MN].600 Rated Power Coefficient Rated Thrust Coefficient The chord and twist distribution for the NREL 5 MW rotor is shown Figure A.3. Figure A.3: Chord and Twist Distribution for the NREL 5 MW Wind Turbine Table A.4: NREL 5 MW Airfoil Locations r/r Airfoil Cylinder Cylinder DU DU DU DU DU NACA64 88

105 Figure A.4: Lift and Drag Coefficient vs Angle of Attack for the Cylinder01 Airfoil Figure A.5: Lift and Drag Coefficient vs Angle of Attack for the Cylinder02 Airfoil Figure A.6: Lift and Drag Coefficient vs Angle of Attack for the DU40 Airfoil Figure A.7: Lift and Drag Coefficient vs Angle of Attack for the DU35 Airfoil 89

106 Figure A.8: Lift and Drag Coefficient vs Angle of Attack for the DU30 Airfoil Figure A.9: Lift and Drag Coefficient vs Angle of Attack for the DU25 Airfoil Figure A.10: Lift and Drag Coefficient vs Angle of Attack for the DU21 Airfoil Figure A.11: Lift and Drag Coefficient vs Angle of Attack for the NACA64 Airfoil 90

107 A.3 PSU 2.5 MW The PSU 2.5 MW rotor parameters are shown in Table 5.2. Table A.5: PSU 2.5W Wind Turbine Parameters Blade Number 3 Blade Radius [m] 45 Rotor RPM Blade Tip Pitch [deg] 0 Rated Wind Speed [m/s] 12 Rated Power [MW] 2.5 Rated Thrust [MN] 1.8 Rated Power Coefficient Rated Thrust Coefficient The chord and twist distribution for the PSU 2.5 MW rotor is shown Figure A.12. Figure A.12: Chord and Twist Distribution for the PSU 2.5 MW Wind Turbine Table A.6: PSU 2.5W Airfoil Locations r/r Airfoil Cylinder Cylinder Cylinder W2401DUT W2350DUT W300DUT W2250DUT W210DUT W180DUT 91

108 Figure A.13: Lift and Drag Coefficient vs Angle of Attack for the Cylinder05 Airfoil Figure A.14: Lift and Drag Coefficient vs Angle of Attack for the Cylinder04 Airfoil Figure A.15: Lift and Drag Coefficient vs Angle of Attack for the Cylinder03 Airfoil 92

109 Figure A.16: Lift and Drag Coefficient vs Angle of Attack for the 00W2401DUT Airfoil Figure A.17: Lift and Drag Coefficient vs Angle of Attack for the 00W2350DUT Airfoil Figure A.18: Lift and Drag Coefficient vs Angle of Attack for the 97W300DUT Airfoil 93

110 Figure A.19: Lift and Drag Coefficient vs Angle of Attack for the 91W2250DUT Airfoil Figure A.20: Lift and Drag Coefficient vs Angle of Attack for the 93W210DUT Airfoil Figure A.21: Lift and Drag Coefficient vs Angle of Attack for the 95W180DUT Airfoil 94

111 Appendix B TIOCS Input Files TIOCS combines XTURB, LEWICE, and the method of updating iced airfoil aerodynamic properties into one single MATLAB script. TIOCS requires three different input files in order to run an icing event on a wind turbine. The three input files are the User Setup, the Rotor Properties, and the Atmospheric Icing Conditions. Each individual input file will be discussed. B.1 TIOCS Input File: User Setup The TIOCS User Setup file is shown in Figure B.1. This file is broken up into four different sub-inputs. 95

112 Figure B.1: Example TIOCS Input File B.1.1 TIOCS User Sub-Input File: Directory Sub-Input The Directory Sub-Input contains information about where the directories necessary for TIOCS to run are located as shown in Figure B.2. This sub-input is necessary to change for first-time setup. Each variable name is described below: code dir: The path to the directory of both XTURB and LEWICE. XTURB and LEWICE must be in the same directory. matlab dir: The path to the directory of where all the TIOCS MATLAB scripts are located. polar dir: The path to the directory of where all of the airfoil polar files are located. 96

113 airf dir: The path to the directory of where all of the airfoil coordinates are located. setup dir: The path to the directory of where all three TIOCS input files are located (User Setup, Rotor Properties, and the Atmospheric Icing Conditions). delta dir: The path to the directory of where all of the Bragg et al. [14] data is located. output dir: The path to the directory of where the user would like TIOCS to store output files. polar figures: The directory name of the polar figures of each airfoil created by TIOCS. radial dir: The directory name in which TIOCS saves the output files of each radial location. xturb output dir: The directory name of where the XTURB output files are stored. xturb input dir: The directory name of where all the XTURB input files are stored. setup: The directory name where all of the setup files are stored. lewice inp: The filename of the LEWICE input file. xturb inp: The filename of the XTURB input file. tiocs inp: The filename of the TIOCS input file. Figure B.2: Example TIOCS Directory Sub-Input File B.1.2 TIOCS User Sub-Input File: Blade Properties Sub-Input The Blade Properties Sub-Input file is where the user can run various radial locations and different RPM and tip pitch angles shown in Figure B.3. This sub-input is required to be changed for different wind turbines. Each variable name is described below: 97

114 radius: User selects what radial stations to ice. (Typically 41 radial stations needed for convergence in BEMT) nominal pitch: The nominal tip pitch setting to adjust the wind turbine to after the icing event is completed. nominal rpm: The nominal RPM setting to adjust the wind turbine to after the icing event is completed. lewice dt: The time step [s] in LEWICE. niter: The number of times to run the icing event. method: XTURB wind turbine performance calculation method (1 for BEMT, 2 for HVM) Figure B.3: Example TIOCS Sub-Input File B.1.3 TIOCS User Sub-Input File: Output Files The Output Files Sub-Input file is where the user can define the name of the TIOCS created output files as well as the file extensions shown in Figure B.4. This sub-input is not necessary to change. Each variable name is described below: out ext: The extension of the output files written by TIOCS. radial out: The filename of the airfoil radial locations written by TIOCS. power out: The filename of the wind turbine performance written by TIOCS. ice out: The filename of the ice mass written by TIOCS. Figure B.4: Example TIOCS Sub-Input File 98

115 B.1.4 TIOCS User Sub-Input File: File Extensions The File Extensions Sub-Input File shown in Figure B.5 is where the user specifies the file extensions of all input files. These are required to be changed and all files must have consistent extensions. Each variable name is described below: polar: The file extension of polar files. out: The file extension of XTURB output files created using method = 2 (HVM) inp: The file extension of TIOCS input files. airf: The file extension of all airfoil coordinates plt: The file extension of XTURB output files created using method = 2 (HVM) dat: The file extension of XTURB (method 1 or 2) and LEWICE output files. Figure B.5: Example TIOCS Sub-Input File B.2 TIOCS Input Files B.2.1 LEWICE Input Files The LEWICE code requires two different input files: the airfoil coordinate file and the atmospheric icing conditions input file. These files are described in the LEWICE manual [13] and an example LEWICE input file is shown in Figure B.6. The parameters that typically need to be edited in a TIOCS run are listed below: ITMFL: This parameter is set to 0 if the user would like LEWICE to calculate the icing time step. If set to 1, the time step is the user specified variable lewice dt from Figure B.3. TSTOP: The length of the icing event [s]. DPD: The size, in microns, of the water drops. If only one size is input, it is the MVD (median volume droplet). For more information, see [13]. 99

116 LWC: the liquid water content of the air in g/m 3. TINF: the ambient static temperature in degrees Kelvin. PINF: the ambient static pressure in Pascals [N/m 2 ]. The parameters that are automatically changed for each radial station by TIOCS are listed below: CHORD: the distance from the leading edge to the trailing edge of the body in meters [m]. AOA: the angle of the body as input with respect to the flow in degrees [ ]. VINF: the ambient velocity (the relative velocity V rel ) in m/s. Figure B.6: Sample Input File for LEWICE [13] 100

117 B.2.2 XTURB Input Files The XTURB code needs two different types of input files. The first required file is the XTURB input file. This input file contains the wind turbine configuration and includes blade number, chord, twist, rotor radius, rotor RPM, etc. For more information on this file, see Schmitz [12]. The second input file(s) are the airfoil polar files and must be in the form of the polar files generated by XFOIL (see [33] for more information). The number of airfoil polars may vary depending on the wind turbine configuration. An example airfoil polar file is shown in Figure B.7. Figure B.7: Sample Airfoil Polar File An example XTURB input file is shown below. XTURB Example Input File &BLADE Name = NREL-PhaseVI, BN = 2, ROOT = 0.25, NTAPER = 2, RTAPER = 0.25, 1.00, CTAPER = , , NTWIST = 21, 101