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Power Generation, Operation, and Control - Allen J. Wood, Bruce F. Wollenberg, Gerald B. Sheblé

Power Generation, Operation, and Control

Buch | Hardcover
656 Seiten
2013 | 3rd edition
Wiley-Interscience (Verlag)
978-0-471-79055-6 (ISBN)
CHF 209,95 inkl. MwSt
Since publication of the second edition, there have been extensive changes in the algorithms, methods, and assumptions in energy management systems that analyze and control power generation. This edition is updated to acquaint electrical engineering students and professionals with current power generation systems.
A thoroughly revised new edition of the definitive work on power systems best practices

In this eagerly awaited new edition, Power Generation, Operation, and Control continues to provide engineers and academics with a complete picture of the techniques used in modern power system operation. Long recognized as the standard reference in the field, the book has been thoroughly updated to reflect the enormous changes that have taken place in the electric power industry since the Second Edition was published seventeen years ago.

With an emphasis on both the engineering and economic aspects of energy management, the Third Edition introduces central "terminal" characteristics for thermal and hydroelectric power generation systems, along with new optimization techniques for tackling real-world operating problems. Readers will find a range of algorithms and methods for performing integrated economic, network, and generating system analysis, as well as modern methods for power system analysis, operation, and control. Special features include:



State-of-the-art topics such as market simulation, multiple market analysis, contract and market bidding, and other business topics
Chapters on generation with limited energy supply, power flow control, power system security, and more
An introduction to regulatory issues, renewable energy, and other evolving topics
New worked examples and end-of-chapter problems
A companion website with additional materials, including MATLAB programs and power system sample data sets

ALLEN J. WOOD joined Power Technologies, Inc., in 1969 as a Principal Engineer and Director. He was a Life Fellow of IEEE and served as an adjunct professor in the Electric Power Engineering graduate program at Rensselaer Polytechnic Institute. Dr. Wood passed away in 2011. BRUCE F. WOLLENBERG joined the University of Minnesota in 1989 and made original contributions to the understanding of electric power market structures. He is a Life Fellow of the IEEE and a member of the National Academy of Engineering. GERALD B. SHEBLÉ joined Auburn University in 1990 to conduct research in power system, space power, and electric auction market research. He joined Iowa State University to conduct research in the interaction of markets and power system operation. His academic research has continued to center on the action of the markets based on the physical operation of the power system. He is a Fellow of the IEEE. Dr. Sheble' passed away in 2021.

Preface to the Third Edition xvii

Preface to the Second Edition xix

Preface to the First Edition xxi

Acknowledgment xxiii

1 Introduction 1

1.1 Purpose of the Course 1

1.2 Course Scope 2

1.3 Economic Importance 2

1.4 Deregulation: Vertical to Horizontal 3

1.5 Problems: New and Old 3

1.6 Characteristics of Steam Units 6

1.6.1 Variations in Steam Unit Characteristics 10

1.6.2 Combined Cycle Units 13

1.6.3 Cogeneration Plants 14

1.6.4 Light-Water Moderated Nuclear Reactor Units 17

1.6.5 Hydroelectric Units 18

1.6.6 Energy Storage 21

1.7 Renewable Energy 22

1.7.1 Wind Power 23

1.7.2 Cut-In Speed 23

1.7.3 Rated Output Power and Rated Output Wind Speed 24

1.7.4 Cut-Out Speed 24

1.7.5 Wind Turbine Efficiency or Power Coefficient 24

1.7.6 Solar Power 25

Appendix 1A Typical Generation Data 26

Appendix 1B Fossil Fuel Prices 28

Appendix 1C Unit Statistics 29

References for Generation Systems 31

Further Reading 31

2 Industrial Organization, Managerial Economics, and Finance 35

2.1 Introduction 35

2.2 Business Environments 36

2.2.1 Regulated Environment 37

2.2.2 Competitive Market Environment 38

2.3 Theory of the Firm 40

2.4 Competitive Market Solutions 42

2.5 Supplier Solutions 45

2.5.1 Supplier Costs 46

2.5.2 Individual Supplier Curves 46

2.5.3 Competitive Environments 47

2.5.4 Imperfect Competition 51

2.5.5 Other Factors 52

2.6 Cost of Electric Energy Production 53

2.7 Evolving Markets 54

2.7.1 Energy Flow Diagram 57

2.8 Multiple Company Environments 58

2.8.1 Leontief Model: Input–Output Economics 58

2.8.2 Scarce Fuel Resources 60

2.9 Uncertainty and Reliability 61

Problems 61

Reference 62

3 Economic Dispatch of Thermal Units and Methods of Solution 63

3.1 The Economic Dispatch Problem 63

3.2 Economic Dispatch with Piecewise Linear Cost Functions 68

3.3 LP Method 69

3.3.1 Piecewise Linear Cost Functions 69

3.3.2 Economic Dispatch with LP 71

3.4 The Lambda Iteration Method 73

3.5 Economic Dispatch Via Binary Search 76

3.6 Economic Dispatch Using Dynamic Programming 78

3.7 Composite Generation Production Cost Function 81

3.8 Base Point and Participation Factors 85

3.9 Thermal System Dispatching with Network Losses Considered 88

3.10 The Concept of Locational Marginal Price (LMP) 92

3.11 Auction Mechanisms 95

3.11.1 PJM Incremental Price Auction as a Graphical Solution 95

3.11.2 Auction Theory Introduction 98

3.11.3 Auction Mechanisms 100

3.11.4 English (First-Price Open-Cry = Ascending) 101

3.11.5 Dutch (Descending) 103

3.11.6 First-Price Sealed Bid 104

3.11.7 Vickrey (Second-Price Sealed Bid) 105

3.11.8 All Pay (e.g., Lobbying Activity) 105

Appendix 3A Optimization Within Constraints 106

Appendix 3B Linear Programming (LP) 117

Appendix 3C Non-Linear Programming 128

Appendix 3D Dynamic Programming (DP) 128

Appendix 3E Convex Optimization 135

Problems 138

References 146

4 Unit Commitment 147

4.1 Introduction 147

4.1.1 Economic Dispatch versus Unit Commitment 147

4.1.2 Constraints in Unit Commitment 152

4.1.3 Spinning Reserve 152

4.1.4 Thermal Unit Constraints 153

4.1.5 Other Constraints 155

4.2 Unit Commitment Solution Methods 155

4.2.1 Priority-List Methods 156

4.2.2 Lagrange Relaxation Solution 157

4.2.3 Mixed Integer Linear Programming 166

4.3 Security-Constrained Unit Commitment (SCUC) 167

4.4 Daily Auctions Using a Unit Commitment 167

Appendix 4A Dual Optimization on a Nonconvex Problem 167

Appendix 4B Dynamic-Programming Solution to Unit Commitment 173

4B.1 Introduction 173

4B.2 Forward DP Approach 174

Problems 182

5 Generation with Limited Energy Supply 187

5.1 Introduction 187

5.2 Fuel Scheduling 188

5.3 Take-or-Pay Fuel Supply Contract 188

5.4 Complex Take-or-Pay Fuel Supply Models 194

5.4.1 Hard Limits and Slack Variables 194

5.5 Fuel Scheduling by Linear Programming 195

5.6 Introduction to Hydrothermal Coordination 202

5.6.1 Long-Range Hydro-Scheduling 203

5.6.2 Short-Range Hydro-Scheduling 204

5.7 Hydroelectric Plant Models 204

5.8 Scheduling Problems 207

5.8.1 Types of Scheduling Problems 207

5.8.2 Scheduling Energy 207

5.9 The Hydrothermal Scheduling Problem 211

5.9.1 Hydro-Scheduling with Storage Limitations 211

5.9.2 Hydro-Units in Series (Hydraulically Coupled) 216

5.9.3 Pumped-Storage Hydroplants 218

5.10 Hydro-Scheduling using Linear Programming 222

Appendix 5A Dynamic-Programming Solution to hydrothermal Scheduling 225

5.A.1 Dynamic Programming Example 227

5.A.1.1 Procedure 228

5.A.1.2 Extension to Other Cases 231

5.A.1.3 Dynamic-Programming Solution to Multiple Hydroplant

Problem 232

Problems 234

6 Transmission System Effects 243

6.1 Introduction 243

6.2 Conversion of Equipment Data to Bus and Branch Data 247

6.3 Substation Bus Processing 248

6.4 Equipment Modeling 248

6.5 Dispatcher Power Flow for Operational Planning 251

6.6 Conservation of Energy (Tellegen’s Theorem) 252

6.7 Existing Power Flow Techniques 253

6.8 The Newton–Raphson Method Using the Augmented Jacobian Matrix 254

6.8.1 Power Flow Statement 254

6.9 Mathematical Overview 257

6.10 AC System Control Modeling 259

6.11 Local Voltage Control 259

6.12 Modeling of Transmission Lines and Transformers 259

6.12.1 Transmission Line Flow Equations 259

6.12.2 Transformer Flow Equations 260

6.13 HVDC links 261

6.13.1 Modeling of HVDC Converters and FACT Devices 264

6.13.2 Definition of Angular Relationships in HVDC Converters 264

6.13.3 Power Equations for a Six-Pole HVDC Converter 264

6.14 Brief Review of Jacobian Matrix Processing 267

6.15 Example 6A: AC Power Flow Case 269

6.16 The Decoupled Power Flow 271

6.17 The Gauss–Seidel Method 275

6.18 The “DC” or Linear Power Flow 277

6.18.1 DC Power Flow Calculation 277

6.18.2 Example 6B: DC Power Flow Example on the Six-Bus Sample System 278

6.19 Unified Eliminated Variable Hvdc Method 278

6.19.1 Changes to Jacobian Matrix Reduced 279

6.19.2 Control Modes 280

6.19.3 Analytical Elimination 280

6.19.4 Control Mode Switching 283

6.19.5 Bipolar and 12-Pulse Converters 283

6.20 Transmission Losses 284

6.20.1 A Two-Generator System Example 284

6.20.2 Coordination Equations, Incremental Losses, and Penalty Factors 286

6.21 Discussion of Reference Bus Penalty Factors 288

6.22 Bus Penalty Factors Direct from the AC Power Flow 289

Problems 291

7 Power System Security 296

7.1 Introduction 296

7.2 Factors Affecting Power System Security 301

7.3 Contingency Analysis: Detection of Network Problems 301

7.3.1 Generation Outages 301

7.3.2 Transmission Outages 302

7.4 An Overview of Security Analysis 306

7.4.1 Linear Sensitivity Factors 307

7.5 Monitoring Power Transactions Using “Flowgates” 313

7.6 Voltage Collapse 315

7.6.1 AC Power Flow Methods 317

7.6.2 Contingency Selection 320

7.6.3 Concentric Relaxation 323

7.6.4 Bounding 325

7.6.5 Adaptive Localization 325

Appendix 7A AC Power Flow Sample Cases 327

Appendix 7B Calculation of Network Sensitivity Factors 336

7B.1 Calculation of PTDF Factors 336

7B.2 Calculation of LODF Factors 339

7B.2.1 Special Cases 341

7B.3 Compensated PTDF Factors 343

Problems 343

References 349

8 Optimal Power Flow 350

8.1 Introduction 350

8.2 The Economic Dispatch Formulation 351

8.3 The Optimal Power Flow Calculation Combining Economic Dispatch and the Power Flow 352

8.4 Optimal Power Flow Using the DC Power Flow 354

8.5 Example 8A: Solution of the DC Power Flow OPF 356

8.6 Example 8B: DCOPF with Transmission Line Limit Imposed 361

8.7 Formal Solution of the DCOPF 365

8.8 Adding Line Flow Constraints to the Linear Programming Solution 365

8.8.1 Solving the DCOPF Using Quadratic Programming 367

8.9 Solution of the ACOPF 368

8.10 Algorithms for Solution of the ACOPF 369

8.11 Relationship Between LMP, Incremental Losses, and Line Flow Constraints 376

8.11.1 Locational Marginal Price at a Bus with No Lines Being Held at Limit 377

8.11.2 Locational Marginal Price with a Line Held at its Limit 378

8.12 Security-Constrained OPF 382

8.12.1 Security Constrained OPF Using the DC Power Flow and Quadratic Programming 384

8.12.2 DC Power Flow 385

8.12.3 Line Flow Limits 385

8.12.4 Contingency Limits 386

Appendix 8A Interior Point Method 391

Appendix 8B Data for the 12-Bus System 393

Appendix 8C Line Flow Sensitivity Factors 395

Appendix 8D Linear Sensitivity Analysis of the AC Power Flow 397

Problems 399

9 Introduction to State Estimation in Power Systems 403

9.1 Introduction 403

9.2 Power System State Estimation 404

9.3 Maximum Likelihood Weighted Least-Squares Estimation 408

9.3.1 Introduction 408

9.3.2 Maximum Likelihood Concepts 410

9.3.3 Matrix Formulation 414

9.3.4 An Example of Weighted Least-Squares State Estimation 417

9.4 State Estimation of an Ac Network 421

9.4.1 Development of Method 421

9.4.2 Typical Results of State Estimation on an AC Network 424

9.5 State Estimation by Orthogonal Decomposition 428

9.5.1 The Orthogonal Decomposition Algorithm 431

9.6 An Introduction to Advanced Topics in State Estimation 435

9.6.1 Sources of Error in State Estimation 435

9.6.2 Detection and Identification of Bad Measurements 436

9.6.3 Estimation of Quantities Not Being Measured 443

9.6.4 Network Observability and Pseudo-measurements 444

9.7 The Use of Phasor Measurement Units (PMUS) 447

9.8 Application of Power Systems State Estimation 451

9.9 Importance of Data Verification and Validation 454

9.10 Power System Control Centers 454

Appendix 9A Derivation of Least-Squares Equations 456

9A.1 The Overdetermined Case (Nm > Ns) 457

9A.2 The Fully Determined Case (Nm = Ns) 462

9A.3 The Underdetermined Case (Nm < Ns) 462

Problems 464

10 Control of Generation 468

10.1 Introduction 468

10.2 Generator Model 470

10.3 Load Model 473

10.4 Prime-Mover Model 475

10.5 Governor Model 476

10.6 Tie-Line Model 481

10.7 Generation Control 485

10.7.1 Supplementary Control Action 485

10.7.2 Tie-Line Control 486

10.7.3 Generation Allocation 489

10.7.4 Automatic Generation Control (AGC) Implementation 491

10.7.5 AGC Features 495

10.7.6 NERC Generation Control Criteria 496

Problems 497

References 500

11 Interchange, Pooling, Brokers, and Auctions 501

11.1 Introduction 501

11.2 Interchange Contracts 504

11.2.1 Energy 504

11.2.2 Dynamic Energy 506

11.2.3 Contingent 506

11.2.4 Market Based 507

11.2.5 Transmission Use 508

11.2.6 Reliability 517

11.3 Energy Interchange between Utilities 517

11.4 Interutility Economy Energy Evaluation 521

11.5 Interchange Evaluation with Unit Commitment 522

11.6 Multiple Utility Interchange Transactions—Wheeling 523

11.7 Power Pools 526

11.8 The Energy-Broker System 529

11.9 Transmission Capability General Issues 533

11.10 Available Transfer Capability and Flowgates 535

11.10.1 Definitions 536

11.10.2 Process 539

11.10.3 Calculation ATC Methodology 540

11.11 Security Constrained Unit Commitment (SCUC) 550

11.11.1 Loads and Generation in a Spot Market Auction 550

11.11.2 Shape of the Two Functions 552

11.11.3 Meaning of the Lagrange Multipliers 553

11.11.4 The Day-Ahead Market Dispatch 554

11.12 Auction Emulation using Network LP 555

11.13 Sealed Bid Discrete Auctions 555

Problems 560

12 Short-Term Demand Forecasting 566

12.1 Perspective 566

12.2 Analytic Methods 569

12.3 Demand Models 571

12.4 Commodity Price Forecasting 572

12.5 Forecasting Errors 573

12.6 System Identification 573

12.7 Econometric Models 574

12.7.1 Linear Environmental Model 574

12.7.2 Weather-Sensitive Models 576

12.8 Time Series 578

12.8.1 Time Series Models Seasonal Component 578

12.8.2 Auto-Regressive (AR) 580

12.8.3 Moving Average (MA) 581

12.8.4 Auto-Regressive Moving Average (ARMA): Box-Jenkins 582

12.8.5 Auto-Regressive Integrated Moving-Average (ARIMA): Box-Jenkins 584

12.8.6 Others (ARMAX, ARIMAX, SARMAX, NARMA) 585

12.9 Time Series Model Development 585

12.9.1 Base Demand Models 586

12.9.2 Trend Models 586

12.9.3 Linear Regression Method 586

12.9.4 Seasonal Models 588

12.9.5 Stationarity 588

12.9.6 WLS Estimation Process 590

12.9.7 Order and Variance Estimation 591

12.9.8 Yule-Walker Equations 592

12.9.9 Durbin-Levinson Algorithm 595

12.9.10 Innovations Estimation for MA and ARMA Processes 598

12.9.11 ARIMA Overall Process 600

12.10 Artificial Neural Networks 603

12.10.1 Introduction to Artificial Neural Networks 604

12.10.2 Artificial Neurons 605

12.10.3 Neural network applications 606

12.10.4 Hopfield Neural Networks 606

12.10.5 Feed-Forward Networks 607

12.10.6 Back-Propagation Algorithm 610

12.10.7 Interior Point Linear Programming Algorithms 613

12.11 Model Integration 614

12.12 Demand Prediction 614

12.12.1 Hourly System Demand Forecasts 615

12.12.2 One-Step Ahead Forecasts 615

12.12.3 Hourly Bus Demand Forecasts 616

12.13 Conclusion 616

Problems 617

Index 620

Erscheint lt. Verlag 24.12.2013
Sprache englisch
Maße 163 x 239 mm
Gewicht 1043 g
Themenwelt Technik Elektrotechnik / Energietechnik
ISBN-10 0-471-79055-9 / 0471790559
ISBN-13 978-0-471-79055-6 / 9780471790556
Zustand Neuware
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