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.

• PREFACE xviiPREFACE TO THE FIRST EDITION xixACKNOWLEDGMENTS xxiAUTHOR BIOGRAPHY xxiiiCHAPTER 1 INTRODUCTION 11.1 Power System Basics 21.2 Conventional Methods 71.3 Intelligent Search Methods 91.4 Application of The Fuzzy Set Theory 10References 10CHAPTER 2 POWER FLOW ANALYSIS 132.1 Mathematical Model of Power Flow 132.2 Newton-Raphson Method 152.3 Gauss-Seidel Method 312.4 P-Q Decoupling Method 332.5 DC Power Flow 432.6 State Estimation 44Problems and Exercises 48References 49CHAPTER 3 SENSITIVITY CALCULATION 513.1 Introduction 513.2 Loss Sensitivity Calculation 523.3 Calculation of Constrained Shift Sensitivity Factors 563.4 Perturbation Method for Sensitivity Analysis 683.5 Voltage Sensitivity Analysis 713.6 Real-Time Application of the Sensitivity Factors 733.7 Simulation Results 743.8 Conclusion 86Problems and Exercises 88References 88CHAPTER 4 CLASSIC ECONOMIC DISPATCH 914.1 Introduction 914.2 Input–Output Characteristics of Generator Units 914.3 Thermal System Economic Dispatch Neglecting Network Losses 974.4 Calculation of Incremental Power Losses 1054.5 Thermal System Economic Dispatch with Network Losses 1074.6 Hydrothermal System Economic Dispatch 1094.7 Economic Dispatch by Gradient Method 1164.8 Classic Economic Dispatch by Genetic Algorithm 1234.9 Classic Economic Dispatch by Hopfield Neural Network 128Appendix A: Optimization Methods Used in Economic Operation 132A.1 Gradient Method 132A.2 Line Search 135A.3 Newton-Raphson Optimization 135A.4 Trust-Region Optimization 136A.5 Newton–Raphson Optimization with Line Search 137A.6 Quasi-Newton Optimization 137A.7 Double Dogleg Optimization 139A.8 Conjugate Gradient Optimization 139A.9 Lagrange Multipliers Method 140A.10 Kuhn–Tucker Conditions 141Problems and Exercises 142References 143CHAPTER 5 SECURITY-CONSTRAINED ECONOMIC DISPATCH 1455.1 Introduction 1455.2 Linear Programming Method 1455.3 Quadratic Programming Method 1575.4 Network Flow Programming Method 1625.5 Nonlinear Convex Network Flow Programming Method 1835.6 Two-Stage Economic Dispatch Approach 1975.7 Security Constrained Economic Dispatch by Genetic Algorithms 201Appendix A: Network Flow Programming 202A.1 The Transportation Problem 203A.2 Dijkstra Label-Setting Algorithm 209Problems and Exercises 210References 212CHAPTER 6 MULTIAREAS SYSTEM ECONOMIC DISPATCH 2156.1 Introduction 2156.2 Economy of Multiareas Interconnection 2156.3 Wheeling 2206.4 Multiarea Wheeling 2256.5 Maed Solved by Nonlinear Convex Network Flow Programming 2266.6 Nonlinear Optimization Neural Network Approach 2356.7 Total Transfer Capability Computation in Multiareas 244Appendix A: Comparison of Two Optimization Neural Network Models 248A.1 For Proposed Neural Network M-9 248A.2 For Neural Network M-10 in Reference [27] 249Problems and Exercises 250References 251CHAPTER 7 UNIT COMMITMENT 2537.1 Introduction 2537.2 Priority Method 2537.3 Dynamic Programming Method 2567.4 Lagrange Relaxation Method 2597.5 Evolutionary Programming-Based Tabu Search Method 2637.6 Particle Swarm Optimization for Unit Commitment 2697.7 Analytic Hierarchy Process 273Problems and Exercises 293References 295CHAPTER 8 OPTIMAL POWER FLOW 2978.1 Introduction 2978.2 Newton Method 2988.3 Gradient Method 3078.4 Linear Programming OPF 3128.5 Modified Interior Point OPF 3148.6 OPF with Phase Shifter 3288.7 Multiple Objectives OPF 3378.8 Particle Swarm Optimization For OPF 346Problems and Exercises 359References 359CHAPTER 9 STEADY-STATE SECURITY REGIONS 3659.1 Introduction 3659.2 Security Corridors 3669.3 Traditional Expansion Method 3719.4 Enhanced Expansion Method 3749.5 Fuzzy Set and Linear Programming 385Appendix A: Linear Programming 391A.1 Standard Form of LP 391A.2 Duality 394A.3 The Simplex Method 397Problems and Exercises 403References 405CHAPTER 10 APPLICATION OF RENEWABLE ENERGY 40710.1 Introduction 40710.2 Renewable Energy Resources 40710.3 Operation of Grid-Connected PV System 40910.4 Voltage Calculation of Distribution Network 41410.5 Frequency Impact of PV Plant in Distribution Network 41710.6 Operation of Wind Energy [1,10–16] 42010.7 Voltage Analysis in Power System with Wind Energy 426Problems and Exercises 432References 434CHAPTER 11 OPTIMAL LOAD SHEDDING 43711.1 Introduction 43711.2 Conventional Load Shedding 43811.3 Intelligent Load Shedding 44011.4 Formulation of Optimal Load Shedding 44311.5 Optimal Load Shedding with Network Constraints 44411.6 Optimal Load Shedding without Network Constraints 45111.7 Distributed Interruptible Load Shedding (DILS) 46011.8 Undervoltage Load Shedding 46711.9 Congestion Management 473Problems and Exercises 480References 481CHAPTER 12 OPTIMAL RECONFIGURATION OF ELECTRICAL DISTRIBUTION NETWORK 48312.1 Introduction 48312.2 Mathematical Model of DNRC 48412.3 Heuristic Methods 48612.4 Rule-Based Comprehensive Approach 48812.5 Mixed-Integer Linear-Programming Approach 49212.6 Application of GA to DNRC 50412.7 Multiobjective Evolution Programming to DNRC 51012.8 Genetic Algorithm Based on Matroid Theory 515Appendix A: Evolutionary Algorithm of Multiobjective Optimization 521Problems and Exercises 524References 526CHAPTER 13 UNCERTAINTY ANALYSIS IN POWER SYSTEMS 52913.1 Introduction 52913.2 Definition of Uncertainty 53013.3 Uncertainty Load Analysis 53013.4 Uncertainty Power Flow Analysis 54213.5 Economic Dispatch with Uncertainties 54513.6 Hydrothermal System Operation with Uncertainty 55513.7 Unit Commitment with Uncertainties 55513.8 VAR Optimization with Uncertain Reactive Load 56113.9 Probabilistic Optimal Power Flow 56313.10 Comparison of Deterministic and Probabilistic Methods 574Problems and Exercises 575References 576CHAPTER 14 OPERATION OF SMART GRID 57914.1 Introduction 57914.2 Definition of Smart Grid 58014.3 Smart Grid Technologies 58014.4 Smart Grid Operation 58114.5 Two-Stage Approach for Smart Grid Dispatch 59714.6 Operation of Virtual Power Plants 60314.7 Smart Distribution Grid 60514.8 Microgrid Operation 60814.9 A New Phase Angle Measurement Algorithm 616Problems and Exercises 623References 626INDEX 629

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.

• PREFACE xviiPREFACE TO THE FIRST EDITION xixACKNOWLEDGMENTS xxiAUTHOR BIOGRAPHY xxiiiCHAPTER 1 INTRODUCTION 11.1 Power System Basics 21.2 Conventional Methods 71.3 Intelligent Search Methods 91.4 Application of The Fuzzy Set Theory 10References 10CHAPTER 2 POWER FLOW ANALYSIS 132.1 Mathematical Model of Power Flow 132.2 Newton-Raphson Method 152.3 Gauss-Seidel Method 312.4 P-Q Decoupling Method 332.5 DC Power Flow 432.6 State Estimation 44Problems and Exercises 48References 49CHAPTER 3 SENSITIVITY CALCULATION 513.1 Introduction 513.2 Loss Sensitivity Calculation 523.3 Calculation of Constrained Shift Sensitivity Factors 563.4 Perturbation Method for Sensitivity Analysis 683.5 Voltage Sensitivity Analysis 713.6 Real-Time Application of the Sensitivity Factors 733.7 Simulation Results 743.8 Conclusion 86Problems and Exercises 88References 88CHAPTER 4 CLASSIC ECONOMIC DISPATCH 914.1 Introduction 914.2 Input–Output Characteristics of Generator Units 914.3 Thermal System Economic Dispatch Neglecting Network Losses 974.4 Calculation of Incremental Power Losses 1054.5 Thermal System Economic Dispatch with Network Losses 1074.6 Hydrothermal System Economic Dispatch 1094.7 Economic Dispatch by Gradient Method 1164.8 Classic Economic Dispatch by Genetic Algorithm 1234.9 Classic Economic Dispatch by Hopfield Neural Network 128Appendix A: Optimization Methods Used in Economic Operation 132A.1 Gradient Method 132A.2 Line Search 135A.3 Newton-Raphson Optimization 135A.4 Trust-Region Optimization 136A.5 Newton–Raphson Optimization with Line Search 137A.6 Quasi-Newton Optimization 137A.7 Double Dogleg Optimization 139A.8 Conjugate Gradient Optimization 139A.9 Lagrange Multipliers Method 140A.10 Kuhn–Tucker Conditions 141Problems and Exercises 142References 143CHAPTER 5 SECURITY-CONSTRAINED ECONOMIC DISPATCH 1455.1 Introduction 1455.2 Linear Programming Method 1455.3 Quadratic Programming Method 1575.4 Network Flow Programming Method 1625.5 Nonlinear Convex Network Flow Programming Method 1835.6 Two-Stage Economic Dispatch Approach 1975.7 Security Constrained Economic Dispatch by Genetic Algorithms 201Appendix A: Network Flow Programming 202A.1 The Transportation Problem 203A.2 Dijkstra Label-Setting Algorithm 209Problems and Exercises 210References 212CHAPTER 6 MULTIAREAS SYSTEM ECONOMIC DISPATCH 2156.1 Introduction 2156.2 Economy of Multiareas Interconnection 2156.3 Wheeling 2206.4 Multiarea Wheeling 2256.5 Maed Solved by Nonlinear Convex Network Flow Programming 2266.6 Nonlinear Optimization Neural Network Approach 2356.7 Total Transfer Capability Computation in Multiareas 244Appendix A: Comparison of Two Optimization Neural Network Models 248A.1 For Proposed Neural Network M-9 248A.2 For Neural Network M-10 in Reference [27] 249Problems and Exercises 250References 251CHAPTER 7 UNIT COMMITMENT 2537.1 Introduction 2537.2 Priority Method 2537.3 Dynamic Programming Method 2567.4 Lagrange Relaxation Method 2597.5 Evolutionary Programming-Based Tabu Search Method 2637.6 Particle Swarm Optimization for Unit Commitment 2697.7 Analytic Hierarchy Process 273Problems and Exercises 293References 295CHAPTER 8 OPTIMAL POWER FLOW 2978.1 Introduction 2978.2 Newton Method 2988.3 Gradient Method 3078.4 Linear Programming OPF 3128.5 Modified Interior Point OPF 3148.6 OPF with Phase Shifter 3288.7 Multiple Objectives OPF 3378.8 Particle Swarm Optimization For OPF 346Problems and Exercises 359References 359CHAPTER 9 STEADY-STATE SECURITY REGIONS 3659.1 Introduction 3659.2 Security Corridors 3669.3 Traditional Expansion Method 3719.4 Enhanced Expansion Method 3749.5 Fuzzy Set and Linear Programming 385Appendix A: Linear Programming 391A.1 Standard Form of LP 391A.2 Duality 394A.3 The Simplex Method 397Problems and Exercises 403References 405CHAPTER 10 APPLICATION OF RENEWABLE ENERGY 40710.1 Introduction 40710.2 Renewable Energy Resources 40710.3 Operation of Grid-Connected PV System 40910.4 Voltage Calculation of Distribution Network 41410.5 Frequency Impact of PV Plant in Distribution Network 41710.6 Operation of Wind Energy [1,10–16] 42010.7 Voltage Analysis in Power System with Wind Energy 426Problems and Exercises 432References 434CHAPTER 11 OPTIMAL LOAD SHEDDING 43711.1 Introduction 43711.2 Conventional Load Shedding 43811.3 Intelligent Load Shedding 44011.4 Formulation of Optimal Load Shedding 44311.5 Optimal Load Shedding with Network Constraints 44411.6 Optimal Load Shedding without Network Constraints 45111.7 Distributed Interruptible Load Shedding (DILS) 46011.8 Undervoltage Load Shedding 46711.9 Congestion Management 473Problems and Exercises 480References 481CHAPTER 12 OPTIMAL RECONFIGURATION OF ELECTRICAL DISTRIBUTION NETWORK 48312.1 Introduction 48312.2 Mathematical Model of DNRC 48412.3 Heuristic Methods 48612.4 Rule-Based Comprehensive Approach 48812.5 Mixed-Integer Linear-Programming Approach 49212.6 Application of GA to DNRC 50412.7 Multiobjective Evolution Programming to DNRC 51012.8 Genetic Algorithm Based on Matroid Theory 515Appendix A: Evolutionary Algorithm of Multiobjective Optimization 521Problems and Exercises 524References 526CHAPTER 13 UNCERTAINTY ANALYSIS IN POWER SYSTEMS 52913.1 Introduction 52913.2 Definition of Uncertainty 53013.3 Uncertainty Load Analysis 53013.4 Uncertainty Power Flow Analysis 54213.5 Economic Dispatch with Uncertainties 54513.6 Hydrothermal System Operation with Uncertainty 55513.7 Unit Commitment with Uncertainties 55513.8 VAR Optimization with Uncertain Reactive Load 56113.9 Probabilistic Optimal Power Flow 56313.10 Comparison of Deterministic and Probabilistic Methods 574Problems and Exercises 575References 576CHAPTER 14 OPERATION OF SMART GRID 57914.1 Introduction 57914.2 Definition of Smart Grid 58014.3 Smart Grid Technologies 58014.4 Smart Grid Operation 58114.5 Two-Stage Approach for Smart Grid Dispatch 59714.6 Operation of Virtual Power Plants 60314.7 Smart Distribution Grid 60514.8 Microgrid Operation 60814.9 A New Phase Angle Measurement Algorithm 616Problems and Exercises 623References 626INDEX 629

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.

• PREFACE xviiPREFACE TO THE FIRST EDITION xixACKNOWLEDGMENTS xxiAUTHOR BIOGRAPHY xxiiiCHAPTER 1 INTRODUCTION 11.1 Power System Basics 21.2 Conventional Methods 71.3 Intelligent Search Methods 91.4 Application of The Fuzzy Set Theory 10References 10CHAPTER 2 POWER FLOW ANALYSIS 132.1 Mathematical Model of Power Flow 132.2 Newton-Raphson Method 152.3 Gauss-Seidel Method 312.4 P-Q Decoupling Method 332.5 DC Power Flow 432.6 State Estimation 44Problems and Exercises 48References 49CHAPTER 3 SENSITIVITY CALCULATION 513.1 Introduction 513.2 Loss Sensitivity Calculation 523.3 Calculation of Constrained Shift Sensitivity Factors 563.4 Perturbation Method for Sensitivity Analysis 683.5 Voltage Sensitivity Analysis 713.6 Real-Time Application of the Sensitivity Factors 733.7 Simulation Results 743.8 Conclusion 86Problems and Exercises 88References 88CHAPTER 4 CLASSIC ECONOMIC DISPATCH 914.1 Introduction 914.2 Input–Output Characteristics of Generator Units 914.3 Thermal System Economic Dispatch Neglecting Network Losses 974.4 Calculation of Incremental Power Losses 1054.5 Thermal System Economic Dispatch with Network Losses 1074.6 Hydrothermal System Economic Dispatch 1094.7 Economic Dispatch by Gradient Method 1164.8 Classic Economic Dispatch by Genetic Algorithm 1234.9 Classic Economic Dispatch by Hopfield Neural Network 128Appendix A: Optimization Methods Used in Economic Operation 132A.1 Gradient Method 132A.2 Line Search 135A.3 Newton-Raphson Optimization 135A.4 Trust-Region Optimization 136A.5 Newton–Raphson Optimization with Line Search 137A.6 Quasi-Newton Optimization 137A.7 Double Dogleg Optimization 139A.8 Conjugate Gradient Optimization 139A.9 Lagrange Multipliers Method 140A.10 Kuhn–Tucker Conditions 141Problems and Exercises 142References 143CHAPTER 5 SECURITY-CONSTRAINED ECONOMIC DISPATCH 1455.1 Introduction 1455.2 Linear Programming Method 1455.3 Quadratic Programming Method 1575.4 Network Flow Programming Method 1625.5 Nonlinear Convex Network Flow Programming Method 1835.6 Two-Stage Economic Dispatch Approach 1975.7 Security Constrained Economic Dispatch by Genetic Algorithms 201Appendix A: Network Flow Programming 202A.1 The Transportation Problem 203A.2 Dijkstra Label-Setting Algorithm 209Problems and Exercises 210References 212CHAPTER 6 MULTIAREAS SYSTEM ECONOMIC DISPATCH 2156.1 Introduction 2156.2 Economy of Multiareas Interconnection 2156.3 Wheeling 2206.4 Multiarea Wheeling 2256.5 Maed Solved by Nonlinear Convex Network Flow Programming 2266.6 Nonlinear Optimization Neural Network Approach 2356.7 Total Transfer Capability Computation in Multiareas 244Appendix A: Comparison of Two Optimization Neural Network Models 248A.1 For Proposed Neural Network M-9 248A.2 For Neural Network M-10 in Reference [27] 249Problems and Exercises 250References 251CHAPTER 7 UNIT COMMITMENT 2537.1 Introduction 2537.2 Priority Method 2537.3 Dynamic Programming Method 2567.4 Lagrange Relaxation Method 2597.5 Evolutionary Programming-Based Tabu Search Method 2637.6 Particle Swarm Optimization for Unit Commitment 2697.7 Analytic Hierarchy Process 273Problems and Exercises 293References 295CHAPTER 8 OPTIMAL POWER FLOW 2978.1 Introduction 2978.2 Newton Method 2988.3 Gradient Method 3078.4 Linear Programming OPF 3128.5 Modified Interior Point OPF 3148.6 OPF with Phase Shifter 3288.7 Multiple Objectives OPF 3378.8 Particle Swarm Optimization For OPF 346Problems and Exercises 359References 359CHAPTER 9 STEADY-STATE SECURITY REGIONS 3659.1 Introduction 3659.2 Security Corridors 3669.3 Traditional Expansion Method 3719.4 Enhanced Expansion Method 3749.5 Fuzzy Set and Linear Programming 385Appendix A: Linear Programming 391A.1 Standard Form of LP 391A.2 Duality 394A.3 The Simplex Method 397Problems and Exercises 403References 405CHAPTER 10 APPLICATION OF RENEWABLE ENERGY 40710.1 Introduction 40710.2 Renewable Energy Resources 40710.3 Operation of Grid-Connected PV System 40910.4 Voltage Calculation of Distribution Network 41410.5 Frequency Impact of PV Plant in Distribution Network 41710.6 Operation of Wind Energy [1,10–16] 42010.7 Voltage Analysis in Power System with Wind Energy 426Problems and Exercises 432References 434CHAPTER 11 OPTIMAL LOAD SHEDDING 43711.1 Introduction 43711.2 Conventional Load Shedding 43811.3 Intelligent Load Shedding 44011.4 Formulation of Optimal Load Shedding 44311.5 Optimal Load Shedding with Network Constraints 44411.6 Optimal Load Shedding without Network Constraints 45111.7 Distributed Interruptible Load Shedding (DILS) 46011.8 Undervoltage Load Shedding 46711.9 Congestion Management 473Problems and Exercises 480References 481CHAPTER 12 OPTIMAL RECONFIGURATION OF ELECTRICAL DISTRIBUTION NETWORK 48312.1 Introduction 48312.2 Mathematical Model of DNRC 48412.3 Heuristic Methods 48612.4 Rule-Based Comprehensive Approach 48812.5 Mixed-Integer Linear-Programming Approach 49212.6 Application of GA to DNRC 50412.7 Multiobjective Evolution Programming to DNRC 51012.8 Genetic Algorithm Based on Matroid Theory 515Appendix A: Evolutionary Algorithm of Multiobjective Optimization 521Problems and Exercises 524References 526CHAPTER 13 UNCERTAINTY ANALYSIS IN POWER SYSTEMS 52913.1 Introduction 52913.2 Definition of Uncertainty 53013.3 Uncertainty Load Analysis 53013.4 Uncertainty Power Flow Analysis 54213.5 Economic Dispatch with Uncertainties 54513.6 Hydrothermal System Operation with Uncertainty 55513.7 Unit Commitment with Uncertainties 55513.8 VAR Optimization with Uncertain Reactive Load 56113.9 Probabilistic Optimal Power Flow 56313.10 Comparison of Deterministic and Probabilistic Methods 574Problems and Exercises 575References 576CHAPTER 14 OPERATION OF SMART GRID 57914.1 Introduction 57914.2 Definition of Smart Grid 58014.3 Smart Grid Technologies 58014.4 Smart Grid Operation 58114.5 Two-Stage Approach for Smart Grid Dispatch 59714.6 Operation of Virtual Power Plants 60314.7 Smart Distribution Grid 60514.8 Microgrid Operation 60814.9 A New Phase Angle Measurement Algorithm 616Problems and Exercises 623References 626INDEX 629