{"product_id":"optimization-of-power-system-operation-isbn-9781118854150","title":"Optimization of Power System Operation","description":"Optimization of Power System Operation, 2\u003csup\u003end\u003c\/sup\u003e 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:\u003cbr\u003e \u003cbr\u003e \u003cul\u003e \u003cli\u003eNew chapter on Application of Renewable Energy, and a new chapter on Operation of Smart Grid\u003c\/li\u003e \u003cli\u003eNew topics include wheeling model, multi-area wheeling, and the total transfer capability computation in multiple areas\u003c\/li\u003e \u003cli\u003eContinues to provide engineers and academics with a complete picture of the optimization of techniques used in modern power system operation\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePREFACE xvii\u003c\/p\u003e \u003cp\u003ePREFACE TO THE FIRST EDITION xix\u003c\/p\u003e \u003cp\u003eACKNOWLEDGMENTS xxi\u003c\/p\u003e \u003cp\u003eAUTHOR BIOGRAPHY xxiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 1 INTRODUCTION 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Power System Basics 2\u003c\/p\u003e \u003cp\u003e1.2 Conventional Methods 7\u003c\/p\u003e \u003cp\u003e1.3 Intelligent Search Methods 9\u003c\/p\u003e \u003cp\u003e1.4 Application of The Fuzzy Set Theory 10\u003c\/p\u003e \u003cp\u003eReferences 10\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 2 POWER FLOW ANALYSIS 13\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Mathematical Model of Power Flow 13\u003c\/p\u003e \u003cp\u003e2.2 Newton-Raphson Method 15\u003c\/p\u003e \u003cp\u003e2.3 Gauss-Seidel Method 31\u003c\/p\u003e \u003cp\u003e2.4 P-Q Decoupling Method 33\u003c\/p\u003e \u003cp\u003e2.5 DC Power Flow 43\u003c\/p\u003e \u003cp\u003e2.6 State Estimation 44\u003c\/p\u003e \u003cp\u003eProblems and Exercises 48\u003c\/p\u003e \u003cp\u003eReferences 49\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 3 SENSITIVITY CALCULATION 51\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 51\u003c\/p\u003e \u003cp\u003e3.2 Loss Sensitivity Calculation 52\u003c\/p\u003e \u003cp\u003e3.3 Calculation of Constrained Shift Sensitivity Factors 56\u003c\/p\u003e \u003cp\u003e3.4 Perturbation Method for Sensitivity Analysis 68\u003c\/p\u003e \u003cp\u003e3.5 Voltage Sensitivity Analysis 71\u003c\/p\u003e \u003cp\u003e3.6 Real-Time Application of the Sensitivity Factors 73\u003c\/p\u003e \u003cp\u003e3.7 Simulation Results 74\u003c\/p\u003e \u003cp\u003e3.8 Conclusion 86\u003c\/p\u003e \u003cp\u003eProblems and Exercises 88\u003c\/p\u003e \u003cp\u003eReferences 88\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 4 CLASSIC ECONOMIC DISPATCH 91\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 91\u003c\/p\u003e \u003cp\u003e4.2 Input–Output Characteristics of Generator Units 91\u003c\/p\u003e \u003cp\u003e4.3 Thermal System Economic Dispatch Neglecting Network Losses 97\u003c\/p\u003e \u003cp\u003e4.4 Calculation of Incremental Power Losses 105\u003c\/p\u003e \u003cp\u003e4.5 Thermal System Economic Dispatch with Network Losses 107\u003c\/p\u003e \u003cp\u003e4.6 Hydrothermal System Economic Dispatch 109\u003c\/p\u003e \u003cp\u003e4.7 Economic Dispatch by Gradient Method 116\u003c\/p\u003e \u003cp\u003e4.8 Classic Economic Dispatch by Genetic Algorithm 123\u003c\/p\u003e \u003cp\u003e4.9 Classic Economic Dispatch by Hopfield Neural Network 128\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: Optimization Methods Used in Economic Operation 132\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Gradient Method 132\u003c\/p\u003e \u003cp\u003eA.2 Line Search 135\u003c\/p\u003e \u003cp\u003eA.3 Newton-Raphson Optimization 135\u003c\/p\u003e \u003cp\u003eA.4 Trust-Region Optimization 136\u003c\/p\u003e \u003cp\u003eA.5 Newton–Raphson Optimization with Line Search 137\u003c\/p\u003e \u003cp\u003eA.6 Quasi-Newton Optimization 137\u003c\/p\u003e \u003cp\u003eA.7 Double Dogleg Optimization 139\u003c\/p\u003e \u003cp\u003eA.8 Conjugate Gradient Optimization 139\u003c\/p\u003e \u003cp\u003eA.9 Lagrange Multipliers Method 140\u003c\/p\u003e \u003cp\u003eA.10 Kuhn–Tucker Conditions 141\u003c\/p\u003e \u003cp\u003eProblems and Exercises 142\u003c\/p\u003e \u003cp\u003eReferences 143\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 5 SECURITY-CONSTRAINED ECONOMIC DISPATCH 145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 145\u003c\/p\u003e \u003cp\u003e5.2 Linear Programming Method 145\u003c\/p\u003e \u003cp\u003e5.3 Quadratic Programming Method 157\u003c\/p\u003e \u003cp\u003e5.4 Network Flow Programming Method 162\u003c\/p\u003e \u003cp\u003e5.5 Nonlinear Convex Network Flow Programming Method 183\u003c\/p\u003e \u003cp\u003e5.6 Two-Stage Economic Dispatch Approach 197\u003c\/p\u003e \u003cp\u003e5.7 Security Constrained Economic Dispatch by Genetic Algorithms 201\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: Network Flow Programming 202\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 The Transportation Problem 203\u003c\/p\u003e \u003cp\u003eA.2 Dijkstra Label-Setting Algorithm 209\u003c\/p\u003e \u003cp\u003eProblems and Exercises 210\u003c\/p\u003e \u003cp\u003eReferences 212\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 6 MULTIAREAS SYSTEM ECONOMIC DISPATCH 215\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 215\u003c\/p\u003e \u003cp\u003e6.2 Economy of Multiareas Interconnection 215\u003c\/p\u003e \u003cp\u003e6.3 Wheeling 220\u003c\/p\u003e \u003cp\u003e6.4 Multiarea Wheeling 225\u003c\/p\u003e \u003cp\u003e6.5 Maed Solved by Nonlinear Convex Network Flow Programming 226\u003c\/p\u003e \u003cp\u003e6.6 Nonlinear Optimization Neural Network Approach 235\u003c\/p\u003e \u003cp\u003e6.7 Total Transfer Capability Computation in Multiareas 244\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: Comparison of Two Optimization Neural Network Models 248\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 For Proposed Neural Network M-9 248\u003c\/p\u003e \u003cp\u003eA.2 For Neural Network M-10 in Reference [27] 249\u003c\/p\u003e \u003cp\u003eProblems and Exercises 250\u003c\/p\u003e \u003cp\u003eReferences 251\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 7 UNIT COMMITMENT 253\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 253\u003c\/p\u003e \u003cp\u003e7.2 Priority Method 253\u003c\/p\u003e \u003cp\u003e7.3 Dynamic Programming Method 256\u003c\/p\u003e \u003cp\u003e7.4 Lagrange Relaxation Method 259\u003c\/p\u003e \u003cp\u003e7.5 Evolutionary Programming-Based Tabu Search Method 263\u003c\/p\u003e \u003cp\u003e7.6 Particle Swarm Optimization for Unit Commitment 269\u003c\/p\u003e \u003cp\u003e7.7 Analytic Hierarchy Process 273\u003c\/p\u003e \u003cp\u003eProblems and Exercises 293\u003c\/p\u003e \u003cp\u003eReferences 295\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 8 OPTIMAL POWER FLOW 297\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 297\u003c\/p\u003e \u003cp\u003e8.2 Newton Method 298\u003c\/p\u003e \u003cp\u003e8.3 Gradient Method 307\u003c\/p\u003e \u003cp\u003e8.4 Linear Programming OPF 312\u003c\/p\u003e \u003cp\u003e8.5 Modified Interior Point OPF 314\u003c\/p\u003e \u003cp\u003e8.6 OPF with Phase Shifter 328\u003c\/p\u003e \u003cp\u003e8.7 Multiple Objectives OPF 337\u003c\/p\u003e \u003cp\u003e8.8 Particle Swarm Optimization For OPF 346\u003c\/p\u003e \u003cp\u003eProblems and Exercises 359\u003c\/p\u003e \u003cp\u003eReferences 359\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 9 STEADY-STATE SECURITY REGIONS 365\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 365\u003c\/p\u003e \u003cp\u003e9.2 Security Corridors 366\u003c\/p\u003e \u003cp\u003e9.3 Traditional Expansion Method 371\u003c\/p\u003e \u003cp\u003e9.4 Enhanced Expansion Method 374\u003c\/p\u003e \u003cp\u003e9.5 Fuzzy Set and Linear Programming 385\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: Linear Programming 391\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Standard Form of LP 391\u003c\/p\u003e \u003cp\u003eA.2 Duality 394\u003c\/p\u003e \u003cp\u003eA.3 The Simplex Method 397\u003c\/p\u003e \u003cp\u003eProblems and Exercises 403\u003c\/p\u003e \u003cp\u003eReferences 405\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 10 APPLICATION OF RENEWABLE ENERGY 407\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 407\u003c\/p\u003e \u003cp\u003e10.2 Renewable Energy Resources 407\u003c\/p\u003e \u003cp\u003e10.3 Operation of Grid-Connected PV System 409\u003c\/p\u003e \u003cp\u003e10.4 Voltage Calculation of Distribution Network 414\u003c\/p\u003e \u003cp\u003e10.5 Frequency Impact of PV Plant in Distribution Network 417\u003c\/p\u003e \u003cp\u003e10.6 Operation of Wind Energy [1,10–16] 420\u003c\/p\u003e \u003cp\u003e10.7 Voltage Analysis in Power System with Wind Energy 426\u003c\/p\u003e \u003cp\u003eProblems and Exercises 432\u003c\/p\u003e \u003cp\u003eReferences 434\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 11 OPTIMAL LOAD SHEDDING 437\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 437\u003c\/p\u003e \u003cp\u003e11.2 Conventional Load Shedding 438\u003c\/p\u003e \u003cp\u003e11.3 Intelligent Load Shedding 440\u003c\/p\u003e \u003cp\u003e11.4 Formulation of Optimal Load Shedding 443\u003c\/p\u003e \u003cp\u003e11.5 Optimal Load Shedding with Network Constraints 444\u003c\/p\u003e \u003cp\u003e11.6 Optimal Load Shedding without Network Constraints 451\u003c\/p\u003e \u003cp\u003e11.7 Distributed Interruptible Load Shedding (DILS) 460\u003c\/p\u003e \u003cp\u003e11.8 Undervoltage Load Shedding 467\u003c\/p\u003e \u003cp\u003e11.9 Congestion Management 473\u003c\/p\u003e \u003cp\u003eProblems and Exercises 480\u003c\/p\u003e \u003cp\u003eReferences 481\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 12 OPTIMAL RECONFIGURATION OF ELECTRICAL DISTRIBUTION NETWORK 483\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 483\u003c\/p\u003e \u003cp\u003e12.2 Mathematical Model of DNRC 484\u003c\/p\u003e \u003cp\u003e12.3 Heuristic Methods 486\u003c\/p\u003e \u003cp\u003e12.4 Rule-Based Comprehensive Approach 488\u003c\/p\u003e \u003cp\u003e12.5 Mixed-Integer Linear-Programming Approach 492\u003c\/p\u003e \u003cp\u003e12.6 Application of GA to DNRC 504\u003c\/p\u003e \u003cp\u003e12.7 Multiobjective Evolution Programming to DNRC 510\u003c\/p\u003e \u003cp\u003e12.8 Genetic Algorithm Based on Matroid Theory 515\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A: Evolutionary Algorithm of Multiobjective Optimization 521\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eProblems and Exercises 524\u003c\/p\u003e \u003cp\u003eReferences 526\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 13 UNCERTAINTY ANALYSIS IN POWER SYSTEMS 529\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 529\u003c\/p\u003e \u003cp\u003e13.2 Definition of Uncertainty 530\u003c\/p\u003e \u003cp\u003e13.3 Uncertainty Load Analysis 530\u003c\/p\u003e \u003cp\u003e13.4 Uncertainty Power Flow Analysis 542\u003c\/p\u003e \u003cp\u003e13.5 Economic Dispatch with Uncertainties 545\u003c\/p\u003e \u003cp\u003e13.6 Hydrothermal System Operation with Uncertainty 555\u003c\/p\u003e \u003cp\u003e13.7 Unit Commitment with Uncertainties 555\u003c\/p\u003e \u003cp\u003e13.8 VAR Optimization with Uncertain Reactive Load 561\u003c\/p\u003e \u003cp\u003e13.9 Probabilistic Optimal Power Flow 563\u003c\/p\u003e \u003cp\u003e13.10 Comparison of Deterministic and Probabilistic Methods 574\u003c\/p\u003e \u003cp\u003eProblems and Exercises 575\u003c\/p\u003e \u003cp\u003eReferences 576\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 14 OPERATION OF SMART GRID 579\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 579\u003c\/p\u003e \u003cp\u003e14.2 Definition of Smart Grid 580\u003c\/p\u003e \u003cp\u003e14.3 Smart Grid Technologies 580\u003c\/p\u003e \u003cp\u003e14.4 Smart Grid Operation 581\u003c\/p\u003e \u003cp\u003e14.5 Two-Stage Approach for Smart Grid Dispatch 597\u003c\/p\u003e \u003cp\u003e14.6 Operation of Virtual Power Plants 603\u003c\/p\u003e \u003cp\u003e14.7 Smart Distribution Grid 605\u003c\/p\u003e \u003cp\u003e14.8 Microgrid Operation 608\u003c\/p\u003e \u003cp\u003e14.9 A New Phase Angle Measurement Algorithm 616\u003c\/p\u003e \u003cp\u003eProblems and Exercises 623\u003c\/p\u003e \u003cp\u003eReferences 626\u003c\/p\u003e \u003cp\u003eINDEX 629\u003c\/p\u003e \u003cb\u003eJizhong Zhu\u003c\/b\u003e 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.  \u003cp\u003eThis book applies the latest applications of new technologies to power system operation and analysis, including new and important areas that are not covered in the previous edition.\u003cbr\u003e \u003cbr\u003e Optimization of Power System Operation covers both traditional and modern technologies, including power flow analysis, steady-state security region analysis, security constrained economic dispatch, multi-area system economic dispatch, unit commitment, optimal power flow, smart grid operation, optimal load shed, optimal reconfiguration of distribution network, power system uncertainty analysis, power system sensitivity analysis, analytic hierarchical process, neural network, fuzzy theory, genetic algorithm, evolutionary programming, and particle swarm optimization, among others.  New topics such as the wheeling model, multi-area wheeling, the total transfer capability computation in multiple areas, are also addressed. \u003cbr\u003e \u003cbr\u003e The new edition of this book continues to provide engineers and academics with a complete picture of the optimization of techniques used in power system operation, several important additions have been made.\u003cbr\u003e \u003cbr\u003e \u003c\/p\u003e \u003cul\u003e \u003cli\u003eAddresses advanced methods and optimization technologies and their applications in power systems\u003c\/li\u003e \u003cli\u003eNew chapters include: Steady State Security Regions, Optimal Load Shedding, Optimal Reconfiguration of Electric Distribution Network, and Uncertainty Analysis in Power Systems\u003c\/li\u003e \u003cli\u003eNew hot topics covered in detail include: Application of Renewable Energy and Operation of Smart Grid\u003c\/li\u003e \u003cli\u003eEnd-of-chapter exercises added\u003c\/li\u003e \u003c\/ul\u003e \u003cbr\u003e Some contents are analyzed and discussed for the first time in detail in this book. Power engineers, operators, and planners will be able to benefit from this insightful source, as well as advanced undergraduate and graduate students.","brand":"Wiley-IEEE Press","offers":[{"title":"Default Title","offer_id":47989723070693,"sku":"NP9781118854150","price":156.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118854150.jpg?v=1761785251","url":"https:\/\/k12savings.com\/products\/optimization-of-power-system-operation-isbn-9781118854150","provider":"K12savings","version":"1.0","type":"link"}