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E-grāmata: Wind Energy Systems: Control Engineering Design

(Case Western Reserve University, Cleveland, Ohio, USA), (Air Force Institute of Technology, Wright-Patterson AFB, Ohio, USA)
  • Formāts: 631 pages
  • Izdošanas datums: 02-Feb-2012
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781439821800
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Wind Energy Systems: Control Engineering DesignPalielināt
  • Formāts: 631 pages
  • Izdošanas datums: 02-Feb-2012
  • Izdevniecība: CRC Press Inc
  • Valoda: eng
  • ISBN-13: 9781439821800
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Presenting the latest developments in the field, Wind Energy Systems: Control Engineering Design offers a novel take on advanced control engineering design techniques for wind turbine applications. The book introduces concurrent quantitative engineering techniques for the design of highly efficient and reliable controllers, which can be used to solve the most critical problems of multi-megawatt wind energy systems.

This book is based on the authors’ experience during the last two decades designing commercial multi-megawatt wind turbines and control systems for industry leaders, including NASA and the European Space Agency. This work is their response to the urgent need for a truly reliable concurrent engineering methodology for the design of advanced control systems. Outlining a roadmap for such a coordinated architecture, the authors consider the links between all aspects of a multi-megawatt wind energy project, in which the wind turbine and the control system must be cooperatively designed to achieve an optimized, reliable, and successful system.

Look inside for links to a free download of QFTCT—a new interactive CAD tool for QFT controller design with MATLAB® that the authors developed with the European Space Agency.

The textbook’s big-picture insights can help students and practicing engineers control and optimize a wind energy system, in which large, flexible, aerodynamic structures are connected to a demanding variable electrical grid and work automatically under very turbulent and unpredictable environmental conditions. The book covers topics including robust QFT control, aerodynamics, mechanical and electrical dynamic modeling, economics, reliability, and efficiency. It also addresses standards, certification, implementation, grid integration, and power quality, as well as environmental and maintenance issues.

To reinforce understanding, the authors present real examples of experimentation with commercial multi-megawatt direct-drive wind turbines, as well as on-shore, offshore, floating, and airborne wind turbine applications. They also offer a unique in-depth exploration of the quantitative feedback theory (QFT)—a proven, successful robust control technique for real-world applications—as well as advanced switching control techniques that help engineers exceed classical linear limitations.

Recenzijas

Garcia-Sanz and Houpis, who both have extensive expertise in major projects in North America and Europe, describe the latest science and technology in wind turbines . The text includes a link to a free download for the CAD tool they utilize SciTech News, Vol. 66, September 2012

Preface xv
Authors xix
1 Introduction
1(14)
1.1 Broad Context and Motivation
1(1)
1.2 Concurrent Engineering: A Road Map for Energy
1(4)
1.3 Quantitative Robust Control
5(2)
1.4 Novel CAD Toolbox for QFT Controller Design
7(1)
1.5 Outline
8(7)
Part I Advanced Robust Control Techniques: QFT and Nonlinear Switching
2 Introduction to QFT
15(14)
2.1 Quantitative Feedback Theory
15(1)
2.2 Why Feedback?
15(2)
2.3 QFT Overview
17(7)
2.3.1 QFT Design Objective
17(1)
2.3.2 Parametric Uncertainty: A Basic Explanation
17(1)
2.3.2.1 Simple Example
17(1)
2.3.2.2 Simple Mathematical Description
18(1)
2.3.3 Control System Performance Specifications
18(2)
2.3.4 QFT Design Overview
20(1)
2.3.5 QFT Basics
21(1)
2.3.6 QFT Design
22(2)
2.4 Insight into the QFT Technique
24(3)
2.4.1 Open-Loop Plant
24(1)
2.4.2 Closed-Loop Formulation
24(1)
2.4.3 Results of Applying the QFT Design Technique
24(1)
2.4.4 Insight into the Use of the NC in the QFT Technique
24(3)
2.5 Benefits of QFT
27(1)
2.6 Summary
28(1)
3 MISO Analog QFT Control System
29(52)
3.1 Introduction
29(1)
3.2 QFT Method (Single-Loop MISO System)
29(2)
3.3 Design Procedure Outline
31(1)
3.4 Minimum-Phase System Performance Specifications
32(4)
3.4.1 Tracking Models
32(4)
3.4.2 Disturbance-Rejection Models
36(1)
3.5 J LTI Plant Models
36(1)
3.6 Plant Templates of P, (s), P(jωi)
37(2)
3.7 Nominal Plant
39(1)
3.8 U-Contour (Stability Bound)
39(2)
3.9 Tracking Bounds BR(jω) on the NC
41(4)
3.10 Disturbance Bounds BD(jωi)
45(8)
3.10.1 Case 1: (d2(t) = D0u-1(t), d1(t) =0)
45(1)
3.10.1.1 Control Ratio
45(1)
3.10.1.2 Disturbance-Response Characteristic
46(1)
3.10.1.3 Application
46(1)
3.10.1.4 Templates
47(2)
3.10.1.5 Rotated NC
49(1)
3.10.1.6 Bounds BD(jω)
49(1)
3.10.2 Case 2:(d1(t) = D0u-1(t), d2(t) = 0)
50(1)
3.10.2.1 Control Ratio
50(1)
3.10.2.2 Disturbance Response Characteristics
50(1)
3.10.2.3 Bounds B0(jω)
51(2)
3.11 Composite Boundary B0(jω)
53(1)
3.12 Shaping of L0(jω)
54(5)
3.13 Guidelines for Shaping L0(jω)
59(1)
3.14 Design of the Prefilter F(s)
60(2)
3.15 Basic Design Procedure for a MISO System
62(3)
3.16 Design Example 1
65(10)
3.17 Design Example 2
75(1)
3.18 Template Generation for Unstable Plants
75(4)
3.19 Summary
79(2)
4 Discrete Quantitative Feedback Technique
81(48)
4.1 Introduction
81(1)
4.2 Bilinear Transformations
82(7)
4.2.1 ω- and ω'-Domain Transformations
82(2)
4.2.2 s-Plane and ω-Plane Relationship
84(1)
4.2.3 s- to z-Plane Transformation: Tustin Transformation
85(4)
4.3 Non-Minimum-Phase Analog Plant
89(4)
4.3.1 Analog QFT Design Procedure for an n.m.p. Plant
91(2)
4.4 Discrete MISO Model with Plant Uncertainty
93(2)
4.5 QFT ω-Domain DIG Design
95(16)
4.5.1 Closed-Loop System Specifications
96(2)
4.5.2 Plant Templates
98(1)
4.5.3 Bounds B(jυ) on L0(jω)
99(1)
4.5.4 Non-Minimum-Phase L0(ω)
100(3)
4.5.5 Synthesizing Lm0(ω)
103(1)
4.5.6 ω =120 Is Too Small
104(3)
4.5.7 Error in the Design
107(3)
4.5.8 Design of the Prefilter F(ω)
110(1)
4.6 Simulation
111(4)
4.7 Basic Design Procedure for a MISO S-D Control System
115(3)
4.8 QFT Technique Applied to the PCT System
118(7)
4.8.1 Introduction to PCT System DIG Technique
118(2)
4.8.2 Simple PCT Example
120(1)
4.8.3 S-D Control System Example
121(2)
4.8.4 PCT System of Figure 4.9
123(2)
4.8.5 PCT Design Summary
125(1)
4.9 Applicability of Design Technique to Other Plants
125(1)
4.10 Designing L(ω) Directly
126(1)
4.11 Summary
126(3)
4.11.1 Minimum-Phase, Non-Minimum-Phase, and Unstable P(s)
126(1)
4.11.2 Digital Controller Implementation
126(1)
4.11.3 Conclusions
127(2)
5 Diagonal MIMO QFT
129(44)
5.1 Introduction
129(1)
5.2 Examples and Motivation
129(8)
5.2.1 MIMO Plant Example
129(4)
5.2.2 Introduction to MIMO Compensation
133(2)
5.2.3 MIMO Compensation
135(2)
5.3 MIMO Systems---Characteristics and Overview
137(6)
5.3.1 Loops Coupling and Controller Structure
137(1)
5.3.1.1 Interaction Analysis
138(2)
5.3.2 Multivariable Poles and Zeros
140(1)
5.3.3 Directionality
140(1)
5.3.3.1 Gain and Phase
140(1)
5.3.3.2 Effect of Poles and Zeros
141(1)
5.3.3.3 Disturbance and Noise Signals
141(1)
5.3.4 Uncertainty
141(1)
5.3.5 Stability
142(1)
5.4 MIMO QFT Control---Overview
143(3)
5.5 Nonsequential Diagonal MIMO QFT (Method 1)
146(15)
5.5.1 Effective MISO Equivalents
147(4)
5.5.2 Effective MISO Loops of the MIMO System
151(1)
5.5.3 Example: The 2 x 2 Plant
151(2)
5.5.4 Performance Bounds
153(5)
5.5.5 Constraints on the Plant Matrix
158(3)
5.6 Sequential Diagonal MIMO QFT (Method 2)
161(4)
5.7 Basically Noninteracting Loops
165(1)
5.8 MIMO QFT with External (Input) Disturbances
166(5)
5.9 Summary
171(2)
6 Non-Diagonal MIMO QFT
173(34)
6.1 Introduction
173(1)
6.2 Non-Diagonal MIMO QFT: A Coupling Minimization Technique (Method 3)
174(5)
6.2.1 Tracking
175(2)
6.2.2 Disturbance Rejection at Plant Input
177(1)
6.2.3 Disturbance Rejection at Plant Output
178(1)
6.3 Coupling Elements
179(2)
6.4 Optimum Non-Diagonal Compensator
181(1)
6.4.1 Tracking
182(1)
6.4.2 Disturbance Rejection at Plant Input
182(1)
6.4.3 Disturbance Rejection at Plant Output
182(1)
6.5 Coupling Effects
182(1)
6.5.1 Tracking
182(1)
6.5.2 Disturbance Rejection at Plant Input
183(1)
6.5.3 Disturbance Rejection at Plant Output
183(1)
6.6 Quality Function of the Designed Compensator
183(1)
6.7 Design Methodology
184(3)
6.7.1 Methodology
184(3)
6.8 Some Practical Issues
187(1)
6.9 Non-Diagonal MIMO QFT: A Generalized Technique (Method 4)
187(1)
6.10 Reformulation
188(7)
6.10.1 Case 1: Reference Tracking and Disturbance Rejection at Plant Output
189(1)
6.10.1.1 Methodology
189(4)
6.10.2 Case 2: Disturbance Rejection at Plant Input
193(1)
6.10.3 Stability Conditions and Final Implementation
194(1)
6.10.3.1 Stability Conditions
194(1)
6.10.3.2 Final Implementation
194(1)
6.11 Translating Matrix Performance Specifications
195(10)
6.11.1 Case n x n
195(1)
6.11.1.1 Tracking
195(1)
6.11.1.2 Disturbance Rejection at Plant Output
195(1)
6.11.1.3 Disturbance Rejection at Plant Input
196(1)
6.11.1.4 Noise Attenuation
196(1)
6.11.1.5 General Expression
196(5)
6.11.2 Case 2 x 2
201(1)
6.11.2.1 Tracking
201(1)
6.11.2.2 Disturbance Rejection at Plant Output
202(1)
6.11.2.3 Disturbance Rejection at Plant Input
203(1)
6.11.2.4 Noise Attenuation
204(1)
6.12 Comparison of Methods 3 and 4
205(1)
6.13 Summary
205(2)
7 QFT for Distributed Parameter Systems
207(20)
7.1 Introduction
207(1)
7.2 Background
207(1)
7.3 Generalized DPS Control System Structure
208(3)
7.4 Extension of Quantitative Feedback Theory to DPS
211(4)
7.4.1 Classical QFT for Lumped Systems
211(2)
7.4.2 QFT for Distributed Parameter Systems
213(2)
7.5 Modeling Approaches for PDE
215(1)
7.6 Examples
216(9)
7.6.1 Bernoulli-Euler Beam
216(1)
7.6.1.1 Definition
216(1)
7.6.1.2 Modeling
217(1)
7.6.1.3 Control Specifications
217(1)
7.6.1.4 Compensator Design
218(1)
7.6.1.5 Simulations
219(1)
7.6.2 Heat Equation Problem
220(1)
7.6.2.1 Definition
220(1)
7.6.2.2 Modeling
221(1)
7.6.2.3 Control Specifications
222(1)
7.6.2.4 Compensator Design
223(1)
7.6.2.5 Simulations
223(2)
7.7 Summary
225(2)
8 Nonlinear Switching Control Techniques
227(18)
8.1 Introduction
227(1)
8.2 System Stability under Switching
227(6)
8.3 Methodology
233(1)
8.4 Examples
234(7)
8.5 Summary
241(4)
Part II Wind Turbine Control
9 Introduction to Wind Energy Systems
245(12)
9.1 Introduction
245(1)
9.2 Birth of Modern Wind Turbines
246(1)
9.3 Market Sizes and Investments
247(1)
9.4 Future Challenges and Opportunities
248(7)
9.4.1 Offshore Wind Turbine Applications (Application 1)
248(1)
9.4.2 Extreme Weather Conditions (Application 2)
249(1)
9.4.3 Airborne Wind Turbines (Application 3)
249(1)
9.4.4 Cost Reduction for Zero Incentive (TC 1)
249(3)
9.4.5 Efficiency Maximization (TC 2)
252(1)
9.4.6 Mechanical Load Attenuation (TC 3)
253(1)
9.4.7 Large-Scale Grid Penetration (TC 4)
254(1)
9.5 Summary
255(2)
10 Standards and Certification for Wind Turbines
257(12)
10.1 Introduction
257(1)
10.2 Standards: Definition and Strategic Value
257(1)
10.3 Standards: Structure and Development
258(1)
10.4 Certification of Wind Turbines
258(6)
10.4.1 Design Evaluation
260(3)
10.4.2 Prototype Testing
263(1)
10.4.3 Manufacturing Evaluation
263(1)
10.4.4 Type Certificate
263(1)
10.4.5 Project Certificate
263(1)
10.5 General Concepts
264(3)
10.5.1 Turbulence Intensity and Wind Classes
264(1)
10.5.2 Wind Speed Distribution
265(1)
10.5.3 Wind Speed Profile
266(1)
10.5.4 Frequency Analysis: Campbell Diagram
266(1)
10.6 Summary
267(2)
11 Wind Turbine Control Objectives and Strategies
269(12)
11.1 Introduction
269(1)
11.2 Control Objectives
269(1)
11.3 Control Strategies
270(5)
11.3.1 Constant-Speed Wind Turbines
270(1)
11.3.2 Variable-Speed Wind Turbines
271(2)
11.3.3 Passive Stall Control
273(1)
11.3.4 Variable Pitch Control
273(1)
11.3.5 Active Stall Control
274(1)
11.4 Control System
275(5)
11.4.1 Sensors
276(1)
11.4.2 Actuators
277(1)
11.4.3 Controller
277(1)
11.4.4 Safety System
277(1)
11.4.5 Main Control Loops
278(1)
11.4.5.1 Torque
278(1)
11.4.5.2 Pitch
279(1)
11.4.5.3 Yaw Angle
279(1)
11.4.6 External Grid
280(1)
11.4.7 Supervisory Control and Data Acquisition
280(1)
11.5 Summary
280(1)
12 Aerodynamics and Mechanical Modeling of Wind Turbines
281(34)
12.1 Introduction
281(1)
12.2 Aerodynamic Models
281(12)
12.2.1 Maximum Aerodynamic Efficiency: Betz Limit
281(5)
12.2.2 Wake Rotation Effect
286(1)
12.2.3 Wind Turbine Blades and Rotor Terminology
287(3)
12.2.3.1 Additional Symbols and Terminology
290(1)
12.2.4 Effect of Drag and Number of Blades
291(1)
12.2.5 Actual Wind Turbines
291(2)
12.3 Mechanical Models
293(20)
12.3.1 Euler-Lagrange Energy-Based Description
293(1)
12.3.1.1 Symbols and Terminology
293(2)
12.3.1.2 Equations of Motion
295(1)
12.3.2 Mechanical Dynamics of Direct-Drive Wind Turbines (Gearless)
295(4)
12.3.3 Mechanical Dynamics of DFIG Wind Turbines (with Gearbox)
299(5)
12.3.4 Wind Turbine Transfer Matrix
304(5)
12.3.5 Rotor Speed Wind Turbine Transfer Functions
309(4)
12.4 Summary
313(2)
13 Electrical Modeling of Wind Turbines
315(16)
13.1 Introduction
315(1)
13.2 Electrical Models
315(9)
13.2.1 Electrical Machine and Park's Transformation
315(2)
13.2.2 Squirrel Cage Induction Generator
317(2)
13.2.3 Doubly Fed Induction Generator
319(2)
13.2.4 Direct-Drive Synchronous Generator
321(3)
13.3 Power Electronic Converters
324(1)
13.4 Power Quality Characteristics
325(2)
13.4.1 Power Flicker
325(1)
13.4.2 Harmonics and Interharmonics
325(1)
13.4.3 Power Peaks
326(1)
13.4.4 Reactive Power and Power Factor
326(1)
13.4.5 Voltage Dips
327(1)
13.5 Wind Farms Integration in the Power System
327(2)
13.5.1 Capacity Factor of a Wind Farm
327(1)
13.5.2 Limited Transmission Capacity
328(1)
13.5.3 Grid Control
328(1)
13.6 Summary
329(2)
14 Advanced Pitch Control System Design
331(24)
14.1 Introduction
331(1)
14.2 QFT Robust Control Design
332(14)
14.2.1 Model, Parameters, and Uncertainty Definition
332(3)
14.2.2 Performance Specifications
335(4)
14.2.3 Controller Loop Shaping
339(1)
14.2.4 Performance Validation
339(4)
14.2.5 A More General/Flexible Model Definition
343(3)
14.3 Nonlinear Switching Multi-Objective Design
346(5)
14.3.1 Model, Parameters, and Uncertainty Definition
346(1)
14.3.2 Performance Specifications
346(1)
14.3.3 Controller Design
347(2)
14.3.4 Performance Validation
349(2)
14.4 Nonlinear Robust Control Design for Large Parameter Variation
351(2)
14.5 Summary
353(2)
15 Experimental Results with the Direct-Drive Wind Turbine TWT-1.65
355(24)
15.1 Introduction
355(1)
15.2 Variable-Speed Direct-Drive Torres Wind Turbine Family
356(10)
15.3 Torres Wind Turbine Pitch and Rotor Speed Control Results
366(2)
15.4 Wind Farm Grid Integration: Torres Wind Turbine Results
368(5)
15.5 Voltage Dip Solutions: Torres Wind Turbine Results
373(3)
15.6 Summary
376(3)
16 Blades Manufacturing: MIMO QFT Control for Industrial Furnaces
379(22)
16.1 Introduction
379(1)
16.2 Composite Materials
379(2)
16.3 Industrial Furnace Description
381(2)
16.4 Furnace Model
383(4)
16.5 Estimation of Furnace Parameters
387(1)
16.6 MIMO QFT Controller Design
388(9)
16.6.1 Model and Parametric Uncertainty
388(3)
16.6.2 Control Specifications
391(1)
16.6.2.1 Robust Stability
391(1)
16.6.2.2 Reference Tracking
391(1)
16.6.2.3 Disturbance Rejection at Plant Input
391(1)
16.6.3 MIMO Design Procedure
391(6)
16.7 Experimental Results
397(2)
16.8 Summary
399(2)
17 Smart Wind Turbine Blades
401(4)
17.1 Introduction
401(1)
17.2 General Description
401(2)
17.3 Some History
403(1)
17.4 Summary
404(1)
18 Offshore Wind Energy: Overview
405(14)
18.1 Introduction
405(1)
18.2 History of Offshore Platforms
406(1)
18.3 Offshore Wind Farms
407(1)
18.4 Offshore Floating Wind Turbines
408(9)
18.5 Summary
417(2)
19 Airborne Wind Energy Systems
419(8)
19.1 Introduction
419(1)
19.2 Overview of Airborne Wind Energy Systems
419(3)
19.3 Eagle System
422(3)
19.4 Summary
425(2)
Appendix A Templates Generation 427(4)
Appendix B Inequality Bound Expressions 431(6)
Appendix C Analytical QFT Bounds 437(18)
Appendix D Essentials for Loop Shaping 455(16)
Appendix E Fragility Analysis with QFT 471(10)
Appendix F QFT Control Toolbox: User's Guide 481(28)
Appendix G Controller Design Examples 509(20)
Appendix H Conversion of Units 529(2)
Problems 531(22)
Answers to Selected Problems 553(6)
References 559(24)
Index 583
Dr. Mario Garcķa-Sanz is Professor at Case Western Reserve University (CWRU), Ohio, the Milton and Tamar Maltz Professor in Energy Innovation, and Director of the Wind Energy and Control Systems Center at CWRU. As Senior Advisor for the President of the M.Torres Group and Professor at the Public University of Navarra, he played a central role in the design and field experimentation of advanced multi-megawatt wind turbines for industry. Dr. Garcķa-Sanz held visiting professorships at the Control Systems Centre, UMIST (UK, 1995); at Oxford University (UK, 1996); at the Jet Propulsion Laboratory NASA-JPL (California, 2004); and at the European Space Agency ESA-ESTEC (The Netherlands, 2008).

He holds 20 industrial patents, has done more than 40 large research projects for industry and space agencies, and is author or coauthor of more than 150 research papers, including the books Quantitative Feedback Theory: Theory and Applications, Taylor & Francis (2006), and Wind Energy Systems: Control Engineering Design, Taylor & Francis (2012).

Dr. Garcķa-Sanz is Subject Editor of the International Journal of Robust and Nonlinear Control, a member of IFAC and IEEE Technical Committees, and served as NATO/RTO Lecture Series Director and as Guest Editor of international journals (Robust control, QFT control, Wind turbine control, Spacecraft control). He was awarded the IEE Heaviside Prize (UK) in 1995 and the BBVA research award (Spain) in 2001. Professor Garcķa-Sanz's main research interest focuses on bridging the gap between advanced control theory and applications, with special emphasis in Energy Innovation, Wind Energy, Space, Environmental and Industrial Applications.
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