Hall_Matthew_MASc_2013_教学案例设计_教学研究_教育专区.pdf

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1、Mooring Line Modelling and Design Optimizationof Floating Offshore Wind TurbinesbyMatthew Thomas Jair HallB.Sc.,University of New Brunswick,2010A Dissertation Submitted in Partial Fulfillment of theRequirements for the Degree ofMASTER OF APPLIED SCIENCEin the Department of Mechanical Engineeringc?Ma

2、tthew Thomas Jair Hall,2013University of VictoriaAll rights reserved.This dissertation may not be reproduced in whole or in part,byphotocopying or other means,without the permission of the author.iiMooring Line Modelling and Design Optimizationof Floating Offshore Wind TurbinesbyMatthew Thomas Jair

3、HallB.Sc.,University of New Brunswick,2010Supervisory CommitteeDr.Brad Buckham,Supervisor(Department of Mechanical Engineering)Dr.Curran Crawford,Supervisor(Department of Mechanical Engineering)iiiSupervisory CommitteeDr.Brad Buckham,Supervisor(Department of Mechanical Engineering)Dr.Curran Crawford

4、,Supervisor(Department of Mechanical Engineering)ABSTRACTFloating offshore wind turbines have the potential to become a significant sourceof affordable renewable energy.However,their strong interactions with both wind-and wave-induced forces raise a number of technical challenges in both modelling a

5、nddesign.This thesis takes aim at some of those challenges.One of the most uncertain modelling areas is the mooring line dynamics,forwhich quasi-static models that neglect hydrodynamic forces and mooring line iner-tia are commonly used.The consequences of using these quasi-static mooring linemodels

6、as opposed to physically-realistic dynamic mooring line models was studiedthrough a suite of comparison tests performed on three floating turbine designs usingtest cases incorporating both steady and stochastic wind and wave conditions.Toperform this comparison,a dynamic finite-element mooring line

7、model was coupledto the floating wind turbine simulator FAST.The results of the comparison studyindicate the need for higher-fidelity dynamic mooring models for all but the moststable support structure configurations.Industry consensus on an optimal floating wind turbine configuration is inhibitedby

8、 the complex support structure design problem;it is difficult to parameterize the fullrange of design options and intuitive tools for navigating the design space are lacking.The notion of an alternative,“hydrodynamics-based”optimization approach,whichwould abstract details of the platform geometry a

9、nd deal instead with hydrodynamicperformance coefficients,was proposed as a way to obtain a more extensive and in-tuitive exploration of the design space.A basis function approach,which representsthe design space by linearly combining the hydrodynamic performance coefficientsivof a diverse set of ba

10、sis platform geometries,was developed as the most straightfor-ward means to that end.Candidate designs were evaluated in the frequency domainusing linearized coefficients for the wind turbine,platform,and mooring system dy-namics,with the platform hydrodynamic coefficients calculated according to li

11、nearhydrodynamic theory.Results obtained for two mooring systems demonstrate thatthe approach captures the basic nature of the design space,but further investiga-tion revealed limitations on the physical interpretability of linearly-combined basisplatform coefficients.A different approach was then t

12、aken for exploring the design space:a geneticalgorithm-based optimization framework.Using a nine-variable support structureparameterization,this framework is able to span a greater extent of the design spacethan previous approaches in the literature.With a frequency-domain dynamics modelthat include

13、s linearized viscous drag forces on the structure and linearized mooringforces,it provides a good treatment of the important physical considerations whilestill being computationally efficient.The genetic algorithm optimization approachprovides a unique ability to visualize the design space.Applicati

14、on of the frameworkto a hypothetical scenario demonstrates the frameworks effectiveness and identifiesmultiple local optima in the design space some of conventional configurations andothers more unusual.By optimizing to minimize both support structure cost androot-mean-square nacelle acceleration,an

15、d plotting the design exploration in termsof these quantities,a Pareto front can be seen.Clear trends are visible in the designsas one moves along the front:designs with three outer cylinders are best below acost of$6M,designs with six outer cylinders are best above a cost of$6M,and heaveplate size

16、increases with support structure cost.The complexity and unconventionalconfiguration of the Pareto optimal designs may indicate a need for improvement inthe frameworks cost model.vContentsSupervisory CommitteeiiAbstractiiiTable of ContentsvList of TablesxList of FiguresxiAcknowledgementsxivDedicatio

17、nxvNomenclaturexvi1Introduction11.1Background.11.2The Floating Wind Turbine Design Problem.31.2.1Stability Classes.41.2.2Other Considerations.51.3State of the Industry.71.3.1Prototyped Designs.71.3.2Conceptual Designs.101.3.3Current Research Areas.111.4Key Contributions.131.5Thesis Outline.142Floati

18、ng Wind Turbine Modelling162.1Introduction to Coupled Floating Wind Turbine Simulation.16vi2.2Wind Turbine Dynamics Modelling.192.2.1Aerodynamic Models.202.2.2Structural Models.212.2.3Current Trends.222.3Platform Hydrodynamics Modelling.222.3.1Hydrodynamic Loadings.232.3.2Strip Theory and Morisons E

19、quation.252.3.3Introduction to Linear Hydrodynamics.262.3.4Frequency-Domain Linear Hydrodynamics.302.3.5Time-Domain Linear Hydrodynamics.322.3.6Higher-Fidelity Hydrodynamics Treatments.352.3.7Current Trends.362.4Mooring Line Dynamics Modelling.372.4.1Force-Displacement Models.372.4.2Quasi-Static Mod

20、els.382.4.3Dynamic Models.382.4.4Current Trends.392.5Third-Party Models Used in This Thesis.392.5.1FAST.392.5.2ProteusDS.412.5.3WAMIT.422.6Modelling Summary.423Evaluating the Adequacy of Quasi-Static Mooring Line Models443.1Introduction.443.2Methodology.473.2.1Coupled Simulator.473.2.2Dynamic Moorin

21、g Model.473.2.3FAST-ProteusDS Coupling.503.2.4Turbine System Descriptions.513.2.5Test Cases.533.3Results.533.3.1Dynamic Model Convergence and Static Equivalence.553.3.2Free Decay Tests.553.3.3Periodic Results-Platform Motions.57vii3.3.4Stochastic Results-Platform Motions.583.3.5Stochastic Results-To

22、wer and Blade Loads.603.4Discussion.613.5Conclusions.634Hydrodynamics-Based Platform Optimization A Basis FunctionApproach694.1Introduction.694.1.1Conventional Geometry-Based Design Space Exploration.704.1.2Hydrodynamics-Based Optimization.714.2Basis Function Optimization Approach.724.2.1Basis Platf

23、orm Designs.734.3Modeling and Evaluation Methodology.744.3.1Hydrodynamic Loads.774.3.2Wind Turbine Loads.774.3.3Mooring System Loads.784.3.4Environmental Conditions.794.3.5Objective Function.794.4Optimal Platform Solutions.804.4.1Result for Slack Catenary Mooring.804.4.2Result for Tension Leg Moorin

24、g.824.5Discussion of Physical Interpretations.844.5.1Intermediate Interpretation.854.5.2Combined Interpretation.864.5.3Interpretation of Optimization Results.874.6Conclusions.895Geometry-Based Support Structure Optimization-A Genetic Algorithm-Based Framework915.1Introduction.915.2Support Structure

25、Parameterization.935.2.1Platform Geometry.935.2.2Mooring System.955.2.3Taut-Mooring Tendon Arms.975.2.4Float-Connecting Truss Members.98viii5.2.5Platform Mass and Ballast.1005.2.6Support Structure Costs.1025.3Modelling and Evaluation Methodology.1055.3.1Platform Hydrodynamics.1055.3.2Wind Turbine.10

26、95.3.3Mooring Lines.1095.4Genetic Algorithm Optimizer.1105.4.1Cumulative Multi-Niching Genetic Algorithm.1105.4.2Optimization Objectives.1125.4.3Constraints.1145.4.4Inputs.1155.4.5Design Evaluation Implementation.1165.5Results.1165.5.1Single-Cylinder Single-Objective Optimization.1185.5.2Single-Cyli

27、nder Multi-Objective Optimization.1235.5.3Full Design Space Single-Objective Optimization.1255.5.4Full Design Space Multi-Objective Optimization.1285.5.5Time-Domain Verification of Global Optimum.1315.6Conclusions.1335.7Future Work.1356Conclusions1376.1Adequacy of Quasi-Static Mooring Models.1376.2B

28、asis Function Platform Optimization.1386.3GA-Based Support Structure Optimization.1396.4Future Work.1406.4.1Adequacy of Quasi-Static Mooring Models.1406.4.2Basis Function Platform Optimization.1406.4.3GA-Based Support Structure Optimization.141Bibliography142Appendix A A Cumulative Multi-Niching Gen

29、etic Algorithm for Mul-timodal Function Optimization149Appendix B Genetic Algorithm Implementation Details and Settings 158ixB.1 Treatment of Discontinuities.158B.2 Treatment of Constraints.159B.3 GA Settings and Functions.160Appendix C Comparison of Framework Model Results to PublishedData162C.1 Co

30、mparison Description.162C.2 Discussion.163xList of TablesTable 2.1NREL offshore 5MW baseline wind turbine properties.18Table 3.1Selected turbine system specifications.52Table 3.2Load cases(LCs)considered.54Table 3.3Initial displacements for load case 1.4.54Table 4.1Basis platform specifications.75Ta

31、ble 4.2Mooring system specifications.78Table 4.3Optimization results.83Table 5.1Platform geometry scheme design variables.95Table 5.2Anchor cost model.105Table 5.3Single cylinder results comparison.119Table 5.4Weightings for singly-cylinder multi-objective optimization runs 123Table 5.5Full design s

32、pace local optima.127Table 5.6Weightings for full design space multi-objective optimization runs128Table 5.7Comparison of frequency-and time-domain results.133Table B.1GA settings.161Table C.1Comparison of support structure properties.163xiList of FiguresFigure 1.1Degrees of freedom of a floating wi

33、nd turbine.4Figure 1.2Floating wind turbine stability classes.5Figure 1.3The Blue H 80 kW mooring-stabilized prototype.8Figure 1.4The Statiol Hywind 2.3 MW ballast-stabilized prototype.8Figure 1.5The Floating Power Plant Poseidon 3x11 kW prototype.9Figure 1.6The SWAY 7 kW prototype.10Figure 1.7The W

34、indFloat buoyancy-stabilized design.11Figure 1.8The Verti-Wind floating VAWT design.12Figure 1.9The DeepWind floating VAWT design.12Figure 2.1Important loads on a floating wind turbine.17Figure 2.2Performance curves for the NREL offshore 5MW baseline windturbine.19Figure 2.3Floating wind turbine coo

35、rdinate system.23Figure 2.4The components of linear hydrodynamics illustrated for a ver-tical cylinder.23Figure 2.5Mooring line anatomy.37Figure 3.1Coordinate systems of the ProteusDS mooring line model.48Figure 3.2Horizontal and vertical fairlead rensions.56Figure 3.3Normalized Horizontal and Verti

36、cal Fairlead Tensions.56Figure 3.4LC 1.4-platform damping ratios.56Figure 3.5LC 4.1-Platform Pitch PSD.58Figure 3.6LC 5.1-platform pitch PSD.58Figure 3.7LC 4.2-platform pitch PSD.66Figure 3.8LC 5.2-platform pitch PSD.66Figure 3.9LC 5.3-platform pitch PSD.66Figure 3.10Damage equivalent loads.67Figure

37、 3.11Extreme loads.67xiiFigure 3.12Selected time series of ITI Energy Barge in LC 5.2.68Figure 3.13Selected time series of MIT/NREL TLP in LC 5.3.68Figure 4.1Sizing algorithm for Ring basis platform design.74Figure 4.2Basis platform geometries for slack catenary mooring.76Figure 4.3Power spectral de

38、nsity plots of the sea states corresponding toeach wind speed.79Figure 4.4Results for slack catenary mooring.81Figure 4.5Pitch added mass for catenary-moored platforms.82Figure 4.6Pitch damping for catenary-moored platforms.82Figure 4.7Pitch wave excitation for catenary-moored platforms.82Figure 4.8

39、Pitch RAO for catenary-moored platforms.82Figure 4.9Results For Tension Leg Mooring.83Figure 4.10Pitch added mass for tension-leg-moored platforms.84Figure 4.11Pitch damping for tension-leg-moored platforms.84Figure 4.12Pitch wave excitation for tension-leg-moored platforms.84Figure 4.13Pitch RAO fo

40、r tension-leg-moored platforms.84Figure 4.14Platform geometries showing an“intermediate”physical inter-pretation(in blue).85Figure 4.15Platform geometries showing a“combined”physical interpre-tation(in blue).85Figure 4.16Pitch added mass of cylinders.86Figure 4.17Pitch damping of cylinders.86Figure

41、4.18Pitch added mass of combined platforms.88Figure 4.19Pitch damping of combined platforms.88Figure 4.20Pitch wave excitation of combined platforms.88Figure 4.21Pitch RAO of combined platforms.88Figure 5.1Vertical cylinder-based platform geometry scheme.94Figure 5.2Demonstration of mooring line lay

42、outs generated by mooringalgorithm for xMvalues varying from-1 to 2.97Figure 5.3Truss scheme for connecting cylinders.99Figure 5.4Platform geometry scheme with ballast and connective structure101Figure 5.5Ballast shifting strategy.102Figure 5.6Loads on floating platform.106xiiiFigure 5.7Design space

43、 exploration of the CMN GA on a sample two-variable objective function.112Figure 5.8Flow diagram of design evaluation implementation.117Figure 5.9Single-cylinder single-objective design space exploration.120Figure 5.10Single cylinder local optima.121Figure 5.11Single-cylinder single-objective perfor

44、mance space.122Figure 5.12Single-cylinder multi-objective design space explorations.123Figure 5.13Single-cylinder multi-objective performance space.124Figure 5.14Full single-objective design space exploration.125Figure 5.15Full design space local optima.126Figure 5.16Full single-objective performanc

45、e space.127Figure 5.17Full multi-objective design space explorations.128Figure 5.18Full multi-objective performance space.129Figure 5.19Spar-buoy surface meshes input to WAMIT.131Figure C.1Hywind RAO comparison.164Figure C.2WindFloat RAO comparison.165xivACKNOWLEDGEMENTSIm grateful to all the people

46、 who helped make my time at UVic a rich learningexperience.Thanks to my supervisors for providing the chance to work in suchan interesting research area.Special thanks to Brad for his fantastic explanationsof the range of technical topics that came up.Special thanks to Curran for hisattentiveness an

47、d ability to provide ideas and direction with perspective and clarity.Thanks to the colleagues-cum-friends Ive met at various conferences,especially theINORE symposium,for the good discussions,fun times,and inspiration of knowinghow many fantastic people are working in similar research directions.Th

48、anks toSebastien Gueydon of MARIN for his expert advice which,delivered over the courseof just two conferences,helped immensely in keeping my research in touch with reality.Thanks to Scott Beatty for being my floating structure hydrodynamics comrade atUVic and for the opportunity to participate in W

49、EC testing in St.Johns.Thanksto all my friends at UVic and elsewhere,for making school and everything else fun.Thanks to my mom and dad for the blessing of their never-failing support.Andthanks to my brother,Stef,for his courage and never-failing positivity.xvDEDICATIONTo the idea that all human con

50、struction rests on a foundation of naturalecosystems,and that these ecosystems should and must be sustained.xviNomenclatureGreekincident wave headingwave elevationddamping ratio of platform motionsbody displacement vectorcomplex amplitude vector of body displacementwater densityanac.standard deviati