Optimization of Power System Operation: (IEEE Press Series on Power and Energy Systems)

Optimization of Power System Operation, 2nd Edition, offers a practical, hands-on guide to theoretical developments and to the application of advanced optimization methods to realistic electric power engineering problems.  The book includes: New chapter on Application of Renewable Energy, and a new chapter on Operation of Smart Grid New topics include wheeling model, multi-area wheeling, and the total transfer capability computation in multiple areas Continues to provide engineers and academics with a complete picture of the optimization of techniques used in modern power system operation

Table of Contents:
PREFACE xvii PREFACE TO THE FIRST EDITION xix ACKNOWLEDGMENTS xxi AUTHOR BIOGRAPHY xxiii CHAPTER 1 INTRODUCTION 1 1.1 Power System Basics 2 1.2 Conventional Methods 7 1.3 Intelligent Search Methods 9 1.4 Application of The Fuzzy Set Theory 10 References 10 CHAPTER 2 POWER FLOW ANALYSIS 13 2.1 Mathematical Model of Power Flow 13 2.2 Newton-Raphson Method 15 2.3 Gauss-Seidel Method 31 2.4 P-Q Decoupling Method 33 2.5 DC Power Flow 43 2.6 State Estimation 44 Problems and Exercises 48 References 49 CHAPTER 3 SENSITIVITY CALCULATION 51 3.1 Introduction 51 3.2 Loss Sensitivity Calculation 52 3.3 Calculation of Constrained Shift Sensitivity Factors 56 3.4 Perturbation Method for Sensitivity Analysis 68 3.5 Voltage Sensitivity Analysis 71 3.6 Real-Time Application of the Sensitivity Factors 73 3.7 Simulation Results 74 3.8 Conclusion 86 Problems and Exercises 88 References 88 CHAPTER 4 CLASSIC ECONOMIC DISPATCH 91 4.1 Introduction 91 4.2 Input–Output Characteristics of Generator Units 91 4.3 Thermal System Economic Dispatch Neglecting Network Losses 97 4.4 Calculation of Incremental Power Losses 105 4.5 Thermal System Economic Dispatch with Network Losses 107 4.6 Hydrothermal System Economic Dispatch 109 4.7 Economic Dispatch by Gradient Method 116 4.8 Classic Economic Dispatch by Genetic Algorithm 123 4.9 Classic Economic Dispatch by Hopfield Neural Network 128 Appendix A: Optimization Methods Used in Economic Operation 132 A.1 Gradient Method 132 A.2 Line Search 135 A.3 Newton-Raphson Optimization 135 A.4 Trust-Region Optimization 136 A.5 Newton–Raphson Optimization with Line Search 137 A.6 Quasi-Newton Optimization 137 A.7 Double Dogleg Optimization 139 A.8 Conjugate Gradient Optimization 139 A.9 Lagrange Multipliers Method 140 A.10 Kuhn–Tucker Conditions 141 Problems and Exercises 142 References 143 CHAPTER 5 SECURITY-CONSTRAINED ECONOMIC DISPATCH 145 5.1 Introduction 145 5.2 Linear Programming Method 145 5.3 Quadratic Programming Method 157 5.4 Network Flow Programming Method 162 5.5 Nonlinear Convex Network Flow Programming Method 183 5.6 Two-Stage Economic Dispatch Approach 197 5.7 Security Constrained Economic Dispatch by Genetic Algorithms 201 Appendix A: Network Flow Programming 202 A.1 The Transportation Problem 203 A.2 Dijkstra Label-Setting Algorithm 209 Problems and Exercises 210 References 212 CHAPTER 6 MULTIAREAS SYSTEM ECONOMIC DISPATCH 215 6.1 Introduction 215 6.2 Economy of Multiareas Interconnection 215 6.3 Wheeling 220 6.4 Multiarea Wheeling 225 6.5 Maed Solved by Nonlinear Convex Network Flow Programming 226 6.6 Nonlinear Optimization Neural Network Approach 235 6.7 Total Transfer Capability Computation in Multiareas 244 Appendix A: Comparison of Two Optimization Neural Network Models 248 A.1 For Proposed Neural Network M-9 248 A.2 For Neural Network M-10 in Reference [27] 249 Problems and Exercises 250 References 251 CHAPTER 7 UNIT COMMITMENT 253 7.1 Introduction 253 7.2 Priority Method 253 7.3 Dynamic Programming Method 256 7.4 Lagrange Relaxation Method 259 7.5 Evolutionary Programming-Based Tabu Search Method 263 7.6 Particle Swarm Optimization for Unit Commitment 269 7.7 Analytic Hierarchy Process 273 Problems and Exercises 293 References 295 CHAPTER 8 OPTIMAL POWER FLOW 297 8.1 Introduction 297 8.2 Newton Method 298 8.3 Gradient Method 307 8.4 Linear Programming OPF 312 8.5 Modified Interior Point OPF 314 8.6 OPF with Phase Shifter 328 8.7 Multiple Objectives OPF 337 8.8 Particle Swarm Optimization For OPF 346 Problems and Exercises 359 References 359 CHAPTER 9 STEADY-STATE SECURITY REGIONS 365 9.1 Introduction 365 9.2 Security Corridors 366 9.3 Traditional Expansion Method 371 9.4 Enhanced Expansion Method 374 9.5 Fuzzy Set and Linear Programming 385 Appendix A: Linear Programming 391 A.1 Standard Form of LP 391 A.2 Duality 394 A.3 The Simplex Method 397 Problems and Exercises 403 References 405 CHAPTER 10 APPLICATION OF RENEWABLE ENERGY 407 10.1 Introduction 407 10.2 Renewable Energy Resources 407 10.3 Operation of Grid-Connected PV System 409 10.4 Voltage Calculation of Distribution Network 414 10.5 Frequency Impact of PV Plant in Distribution Network 417 10.6 Operation of Wind Energy [1,10–16] 420 10.7 Voltage Analysis in Power System with Wind Energy 426 Problems and Exercises 432 References 434 CHAPTER 11 OPTIMAL LOAD SHEDDING 437 11.1 Introduction 437 11.2 Conventional Load Shedding 438 11.3 Intelligent Load Shedding 440 11.4 Formulation of Optimal Load Shedding 443 11.5 Optimal Load Shedding with Network Constraints 444 11.6 Optimal Load Shedding without Network Constraints 451 11.7 Distributed Interruptible Load Shedding (DILS) 460 11.8 Undervoltage Load Shedding 467 11.9 Congestion Management 473 Problems and Exercises 480 References 481 CHAPTER 12 OPTIMAL RECONFIGURATION OF ELECTRICAL DISTRIBUTION NETWORK 483 12.1 Introduction 483 12.2 Mathematical Model of DNRC 484 12.3 Heuristic Methods 486 12.4 Rule-Based Comprehensive Approach 488 12.5 Mixed-Integer Linear-Programming Approach 492 12.6 Application of GA to DNRC 504 12.7 Multiobjective Evolution Programming to DNRC 510 12.8 Genetic Algorithm Based on Matroid Theory 515 Appendix A: Evolutionary Algorithm of Multiobjective Optimization 521 Problems and Exercises 524 References 526 CHAPTER 13 UNCERTAINTY ANALYSIS IN POWER SYSTEMS 529 13.1 Introduction 529 13.2 Definition of Uncertainty 530 13.3 Uncertainty Load Analysis 530 13.4 Uncertainty Power Flow Analysis 542 13.5 Economic Dispatch with Uncertainties 545 13.6 Hydrothermal System Operation with Uncertainty 555 13.7 Unit Commitment with Uncertainties 555 13.8 VAR Optimization with Uncertain Reactive Load 561 13.9 Probabilistic Optimal Power Flow 563 13.10 Comparison of Deterministic and Probabilistic Methods 574 Problems and Exercises 575 References 576 CHAPTER 14 OPERATION OF SMART GRID 579 14.1 Introduction 579 14.2 Definition of Smart Grid 580 14.3 Smart Grid Technologies 580 14.4 Smart Grid Operation 581 14.5 Two-Stage Approach for Smart Grid Dispatch 597 14.6 Operation of Virtual Power Plants 603 14.7 Smart Distribution Grid 605 14.8 Microgrid Operation 608 14.9 A New Phase Angle Measurement Algorithm 616 Problems and Exercises 623 References 626 INDEX 629

About the Author :
Jizhong Zhu is a Senior Principal Power Systems Engineer as well as a Fellow with ALSTOM Grid Inc, USA. In addition to his industry experience, Dr. Zhu has worked at Howard University in Washington, D.C., the National University of Singapore, Brunel University in England, and Chongqing University in China. A Senior Member of the IEEE and an honorable advisory professor of Chongqing University, he has published six books as an author and co-author, as well as about two hundred papers in the international journals and conferences. His research interest is in the analysis, operation, planning and control of power systems as well as applications of renewable energy.