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
Autorentext
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.
Zusammenfassung
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
Inhalt
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 InputOutput 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 NewtonRaphson 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 KuhnTucker 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 Hierarch...