{"product_id":"dynamic-vulnerability-assessment-and-intelligent-control-9781119214953","title":"Dynamic Vulnerability Assessment and Intelligent","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eIdentifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks.\u003c\/p\u003e \u003cp\u003eKey features:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eIntroduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management.\u003c\/li\u003e \u003cli\u003eProvides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability assessment methods, supported by the underpinning mathematics.\u003c\/li\u003e \u003cli\u003eDevelo\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eList of Contributors xv\u003c\/p\u003e \u003cp\u003eForeword xix\u003c\/p\u003e \u003cp\u003ePreface xxi\u003c\/p\u003e \u003cp\u003e1 Introduction: The Role of Wide Area Monitoring Systems in Dynamic Vulnerability Assessment 1\u003c\/p\u003e \u003cp\u003eJaime C. Cepeda and José Luis Rueda-Torres\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 Power System Vulnerability 2\u003c\/p\u003e \u003cp\u003e1.2.1 Vulnerability Assessment 2\u003c\/p\u003e \u003cp\u003e1.2.2 Timescale of Power System Actions and Operations 4\u003c\/p\u003e \u003cp\u003e1.3 Power System Vulnerability Symptoms 5\u003c\/p\u003e \u003cp\u003e1.3.1 Rotor Angle Stability 6\u003c\/p\u003e \u003cp\u003e1.3.2 Short-Term Voltage Stability 7\u003c\/p\u003e \u003cp\u003e1.3.3 Short-Term Frequency Stability 7\u003c\/p\u003e \u003cp\u003e1.3.4 Post-Contingency Overloads 7\u003c\/p\u003e \u003cp\u003e1.4 Synchronized Phasor Measurement Technology 8\u003c\/p\u003e \u003cp\u003e1.4.1 Phasor Representation of Sinusoids 8\u003c\/p\u003e \u003cp\u003e1.4.2 Synchronized Phasors 9\u003c\/p\u003e \u003cp\u003e1.4.3 Phasor Measurement Units (PMUs) 9\u003c\/p\u003e \u003cp\u003e1.4.4 Discrete Fourier Transform and Phasor Calculation 10\u003c\/p\u003e \u003cp\u003e1.4.5 Wide Area Monitoring Systems 10\u003c\/p\u003e \u003cp\u003e1.4.6 WAMPAC Communication Time Delay 12\u003c\/p\u003e \u003cp\u003e1.5 The Fundamental Role of WAMS in Dynamic Vulnerability Assessment 13\u003c\/p\u003e \u003cp\u003e1.6 Concluding Remarks 16\u003c\/p\u003e \u003cp\u003e2 Steady-state Security 21\u003c\/p\u003e \u003cp\u003eEvelyn Heylen, Steven De Boeck, Marten Ovaere, Hakan Ergun, and Dirk Van Hertem\u003c\/p\u003e \u003cp\u003e2.1 Power System Reliability Management: A Combination of Reliability Assessment and Reliability Control 22\u003c\/p\u003e \u003cp\u003e2.1.1 Reliability Assessment 23\u003c\/p\u003e \u003cp\u003e2.1.2 Reliability Control 24\u003c\/p\u003e \u003cp\u003e2.2 Reliability Under Various Timeframes 31\u003c\/p\u003e \u003cp\u003e2.3 Reliability Criteria 33\u003c\/p\u003e \u003cp\u003e2.4 Reliability and Its Cost as a Function of Uncertainty 34\u003c\/p\u003e \u003cp\u003e2.4.1 Reliability Costs 34\u003c\/p\u003e \u003cp\u003e2.4.2 Interruption Costs 35\u003c\/p\u003e \u003cp\u003e2.4.3 Minimizing the Sum of Reliability and Interruption Costs 36\u003c\/p\u003e \u003cp\u003e3 Probabilistic Indicators for the Assessment of Reliability and Security of Future Power Systems 41\u003c\/p\u003e \u003cp\u003eBart W. Tuinema, Nikoleta Kandalepa, and José Luis Rueda-Torres\u003c\/p\u003e \u003cp\u003e3.1 Introduction 41\u003c\/p\u003e \u003cp\u003e3.2 Time Horizons in the Planning and Operation of Power Systems 42\u003c\/p\u003e \u003cp\u003e3.2.1 Time Horizons 42\u003c\/p\u003e \u003cp\u003e3.2.2 Overlapping and Interaction 42\u003c\/p\u003e \u003cp\u003e3.2.3 Remedial Actions 42\u003c\/p\u003e \u003cp\u003e3.3 Reliability Indicators 45\u003c\/p\u003e \u003cp\u003e3.3.1 Security-of-Supply Related Indicators 45\u003c\/p\u003e \u003cp\u003e3.3.2 Additional Indicators 47\u003c\/p\u003e \u003cp\u003e3.4 Reliability Analysis 49\u003c\/p\u003e \u003cp\u003e3.4.1 Input Information 49\u003c\/p\u003e \u003cp\u003e3.4.2 Pre-calculations 50\u003c\/p\u003e \u003cp\u003e3.4.3 Reliability Analysis 50\u003c\/p\u003e \u003cp\u003e3.4.4 Output: Reliability Indicators 53\u003c\/p\u003e \u003cp\u003e3.5 Application Example: EHV Underground Cables 53\u003c\/p\u003e \u003cp\u003e3.5.1 Input Parameters 54\u003c\/p\u003e \u003cp\u003e3.5.2 Results of Analysis 56\u003c\/p\u003e \u003cp\u003e4 An Enhanced WAMS-based Power System Oscillation Analysis Approach 63\u003c\/p\u003e \u003cp\u003eQing Liu, Hassan Bevrani, and Yasunori Mitani\u003c\/p\u003e \u003cp\u003e4.1 Introduction 63\u003c\/p\u003e \u003cp\u003e4.2 HHT Method 65\u003c\/p\u003e \u003cp\u003e4.2.1 EMD 65\u003c\/p\u003e \u003cp\u003e4.2.2 Hilbert Transform 65\u003c\/p\u003e \u003cp\u003e4.2.3 Hilbert Spectrum and Hilbert Marginal Spectrum 66\u003c\/p\u003e \u003cp\u003e4.2.4 HHT Issues 67\u003c\/p\u003e \u003cp\u003e4.3 The Enhanced HHT Method 71\u003c\/p\u003e \u003cp\u003e4.3.1 Data Pre-treatment Processing 71\u003c\/p\u003e \u003cp\u003e4.3.2 Inhibiting the Boundary End Effect 75\u003c\/p\u003e \u003cp\u003e4.3.3 Parameter Identification 80\u003c\/p\u003e \u003cp\u003e4.4 Enhanced HHT Method Evaluation 81\u003c\/p\u003e \u003cp\u003e4.4.1 Case I 81\u003c\/p\u003e \u003cp\u003e4.4.2 Case II 84\u003c\/p\u003e \u003cp\u003e4.4.3 Case III 85\u003c\/p\u003e \u003cp\u003e4.5 Application to RealWide Area Measurements 88\u003c\/p\u003e \u003cp\u003e5 Pattern Recognition-Based Approach for Dynamic Vulnerability Status Prediction 95\u003c\/p\u003e \u003cp\u003eJaime C. Cepeda, José Luis Rueda-Torres, Delia G. Colomé, and István Erlich\u003c\/p\u003e \u003cp\u003e5.1 Introduction 95\u003c\/p\u003e \u003cp\u003e5.2 Post-contingency Dynamic Vulnerability Regions 96\u003c\/p\u003e \u003cp\u003e5.3 Recognition of Post-contingency DVRs 97\u003c\/p\u003e \u003cp\u003e5.3.1 N-1 Contingency Monte Carlo Simulation 98\u003c\/p\u003e \u003cp\u003e5.3.2 Post-contingency Pattern Recognition Method 100\u003c\/p\u003e \u003cp\u003e5.3.3 Definition of Data-TimeWindows 103\u003c\/p\u003e \u003cp\u003e5.3.4 Identification of Post-contingency DVRs—Case Study 104\u003c\/p\u003e \u003cp\u003e5.4 Real-Time Vulnerability Status Prediction 109\u003c\/p\u003e \u003cp\u003e5.4.1 Support Vector Classifier (SVC) Training 112\u003c\/p\u003e \u003cp\u003e5.4.2 SVC Real-Time Implementation 113\u003c\/p\u003e \u003cp\u003e5.5 Concluding Remarks 115\u003c\/p\u003e \u003cp\u003e6 Performance Indicator-Based Real-Time Vulnerability Assessment 119\u003c\/p\u003e \u003cp\u003eJaime C. Cepeda, José Luis Rueda-Torres, Delia G. Colomé, and István Erlich\u003c\/p\u003e \u003cp\u003e6.1 Introduction 119\u003c\/p\u003e \u003cp\u003e6.2 Overview of the Proposed Vulnerability Assessment Methodology 120\u003c\/p\u003e \u003cp\u003e6.3 Real-Time Area Coherency Identification 122\u003c\/p\u003e \u003cp\u003e6.3.1 Associated PMU Coherent Areas 122\u003c\/p\u003e \u003cp\u003e6.4 TVFS Vulnerability Performance Indicators 125\u003c\/p\u003e \u003cp\u003e6.4.1 Transient Stability Index (TSI) 125\u003c\/p\u003e \u003cp\u003e6.4.2 Voltage Deviation Index (VDI) 128\u003c\/p\u003e \u003cp\u003e6.4.3 Frequency Deviation Index (FDI) 131\u003c\/p\u003e \u003cp\u003e6.4.4 Assessment of TVFS Security Level for the Illustrative Examples 131\u003c\/p\u003e \u003cp\u003e6.4.5 Complete TVFS Real-Time Vulnerability Assessment 133\u003c\/p\u003e \u003cp\u003e6.5 Slower Phenomena Vulnerability Performance Indicators 137\u003c\/p\u003e \u003cp\u003e6.5.1 Oscillatory Index (OSI) 137\u003c\/p\u003e \u003cp\u003e6.5.2 Overload Index (OVI) 141\u003c\/p\u003e \u003cp\u003e6.6 Concluding Remarks 145\u003c\/p\u003e \u003cp\u003e7 Challenges Ahead Risk-Based AC Optimal Power Flow Under Uncertainty for Smart Sustainable Power Systems 149\u003c\/p\u003e \u003cp\u003eFlorin Capitanescu\u003c\/p\u003e \u003cp\u003e7.1 Chapter Overview 149\u003c\/p\u003e \u003cp\u003e7.2 Conventional (Deterministic) AC Optimal Power Flow (OPF) 150\u003c\/p\u003e \u003cp\u003e7.2.1 Introduction 150\u003c\/p\u003e \u003cp\u003e7.2.2 Abstract Mathematical Formulation of the OPF Problem 150\u003c\/p\u003e \u003cp\u003e7.2.3 OPF Solution via Interior-Point Method 151\u003c\/p\u003e \u003cp\u003e7.2.4 Illustrative Example 154\u003c\/p\u003e \u003cp\u003e7.3 Risk-Based OPF 158\u003c\/p\u003e \u003cp\u003e7.3.1 Motivation and Principle 158\u003c\/p\u003e \u003cp\u003e7.3.2 Risk-Based OPF Problem Formulation 159\u003c\/p\u003e \u003cp\u003e7.3.3 Illustrative Example 160\u003c\/p\u003e \u003cp\u003e7.4 OPF Under Uncertainty 162\u003c\/p\u003e \u003cp\u003e7.4.1 Motivation and Potential Approaches 162\u003c\/p\u003e \u003cp\u003e7.4.2 Robust Optimization Framework 162\u003c\/p\u003e \u003cp\u003e7.4.3 Methodology for Solving the R-OPF Problem 163\u003c\/p\u003e \u003cp\u003e7.4.4 Illustrative Example 164\u003c\/p\u003e \u003cp\u003e7.5 Advanced Issues and Outlook 169\u003c\/p\u003e \u003cp\u003e7.5.1 Conventional OPF 169\u003c\/p\u003e \u003cp\u003e7.5.2 Beyond the Scope of Conventional OPF: Risk, Uncertainty, Smarter Sustainable Grid 172\u003c\/p\u003e \u003cp\u003e8 Modeling Preventive and Corrective Actions Using Linear Formulation 177\u003c\/p\u003e \u003cp\u003eTom Van Acker and Dirk Van Hertem\u003c\/p\u003e \u003cp\u003e8.1 Introduction 177\u003c\/p\u003e \u003cp\u003e8.2 Security Constrained OPF 178\u003c\/p\u003e \u003cp\u003e8.3 Available Control Actions in AC Power Systems 178\u003c\/p\u003e \u003cp\u003e8.3.1 Generator Redispatch 179\u003c\/p\u003e \u003cp\u003e8.3.2 Load Shedding and Demand Side Management 179\u003c\/p\u003e \u003cp\u003e8.3.3 Phase Shifting Transformer 179\u003c\/p\u003e \u003cp\u003e8.3.4 Switching Actions 180\u003c\/p\u003e \u003cp\u003e8.3.5 Reactive Power Management 180\u003c\/p\u003e \u003cp\u003e8.3.6 Special Protection Schemes 180\u003c\/p\u003e \u003cp\u003e8.4 Linear Implementation of Control Actions in a SCOPF Environment 180\u003c\/p\u003e \u003cp\u003e8.4.1 Generator Redispatch 181\u003c\/p\u003e \u003cp\u003e8.4.2 Load Shedding and Demand Side Management 182\u003c\/p\u003e \u003cp\u003e8.4.3 Phase Shifting Transformer 183\u003c\/p\u003e \u003cp\u003e8.4.4 Switching 184\u003c\/p\u003e \u003cp\u003e8.5 Case Study of Preventive and Corrective Actions 185\u003c\/p\u003e \u003cp\u003e8.5.1 Case Study 1: Generator Redispatch and Load Shedding (CS1) 186\u003c\/p\u003e \u003cp\u003e8.5.2 Case Study 2: Generator Redispatch, Load Shedding and PST (CS2) 187\u003c\/p\u003e \u003cp\u003e8.5.3 Case Study 3: Generator Redispatch, Load Shedding and Switching (CS3) 190\u003c\/p\u003e \u003cp\u003e9 Model-based Predictive Control for Damping Electromechanical Oscillations in Power Systems 193\u003c\/p\u003e \u003cp\u003eDaWang\u003c\/p\u003e \u003cp\u003e9.1 Introduction 193\u003c\/p\u003e \u003cp\u003e9.2 MPC BasicTheory \u0026amp; Damping Controller Models 194\u003c\/p\u003e \u003cp\u003e9.2.1 What is MPC? 194\u003c\/p\u003e \u003cp\u003e9.2.2 Damping Controller Models 196\u003c\/p\u003e \u003cp\u003e9.3 MPC for Damping Oscillations 198\u003c\/p\u003e \u003cp\u003e9.3.1 Outline of Idea 198\u003c\/p\u003e \u003cp\u003e9.3.2 Mathematical Formulation 199\u003c\/p\u003e \u003cp\u003e9.3.3 Proposed Control Schemes 200\u003c\/p\u003e \u003cp\u003e9.4 Test System \u0026amp; Simulation Setting 204\u003c\/p\u003e \u003cp\u003e9.5 Performance Analysis of MPC Schemes 204\u003c\/p\u003e \u003cp\u003e9.5.1 Centralized MPC 204\u003c\/p\u003e \u003cp\u003e9.5.2 Distributed MPC 209\u003c\/p\u003e \u003cp\u003e9.5.3 Hierarchical MPC 209\u003c\/p\u003e \u003cp\u003e9.6 Conclusions and Discussions 213\u003c\/p\u003e \u003cp\u003e10 Voltage Stability Enhancement by Computational Intelligence Methods 217\u003c\/p\u003e \u003cp\u003eWorawat Nakawiro\u003c\/p\u003e \u003cp\u003e10.1 Introduction 217\u003c\/p\u003e \u003cp\u003e10.2 Theoretical Background 218\u003c\/p\u003e \u003cp\u003e10.2.1 Voltage Stability Assessment 218\u003c\/p\u003e \u003cp\u003e10.2.2 Sensitivity Analysis 219\u003c\/p\u003e \u003cp\u003e10.2.3 Optimal Power Flow 220\u003c\/p\u003e \u003cp\u003e10.2.4 Artificial Neural Network 220\u003c\/p\u003e \u003cp\u003e10.2.5 Ant Colony Optimisation 221\u003c\/p\u003e \u003cp\u003e10.3 Test Power System 223\u003c\/p\u003e \u003cp\u003e10.4 Example 1: Preventive Measure 224\u003c\/p\u003e \u003cp\u003e10.4.1 Problem Statement 224\u003c\/p\u003e \u003cp\u003e10.4.2 Simulation Results 225\u003c\/p\u003e \u003cp\u003e10.5 Example 2: Corrective Measure 226\u003c\/p\u003e \u003cp\u003e10.5.1 Problem Statement 226\u003c\/p\u003e \u003cp\u003e10.5.2 Simulation Results 227\u003c\/p\u003e \u003cp\u003e11 Knowledge-Based Primary and Optimization-Based Secondary Control of Multi-terminal HVDCGrids 233\u003c\/p\u003e \u003cp\u003eAdedotun J. Agbemuko, Mario Ndreko, Marjan Popov, José Luis Rueda-Torres, and Mart A.M.M van der Meijden\u003c\/p\u003e \u003cp\u003e11.1 Introduction 234\u003c\/p\u003e \u003cp\u003e11.2 Conventional Control Schemes in HV-MTDC Grids 234\u003c\/p\u003e \u003cp\u003e11.3 Principles of Fuzzy-Based Control 236\u003c\/p\u003e \u003cp\u003e11.4 Implementation of the Knowledge-Based Power-Voltage Droop Control Strategy 236\u003c\/p\u003e \u003cp\u003e11.4.1 Control Scheme for Primary and Secondary Power-Voltage Control 237\u003c\/p\u003e \u003cp\u003e11.4.2 Input\/Output Variables 238\u003c\/p\u003e \u003cp\u003e11.4.3 Knowledge Base and Inference Engine 241\u003c\/p\u003e \u003cp\u003e11.4.4 Defuzzification and Output 241\u003c\/p\u003e \u003cp\u003e11.5 Optimization-Based Secondary Control Strategy 242\u003c\/p\u003e \u003cp\u003e11.5.1 Fitness Function 242\u003c\/p\u003e \u003cp\u003e11.5.2 Constraints 244\u003c\/p\u003e \u003cp\u003e11.6 Simulation Results 245\u003c\/p\u003e \u003cp\u003e11.6.1 Set Point Change 245\u003c\/p\u003e \u003cp\u003e11.6.2 Constantly Changing Reference Set Points 246\u003c\/p\u003e \u003cp\u003e11.6.3 Sudden Disconnection ofWind Farm for Undefined Period 246\u003c\/p\u003e \u003cp\u003e11.6.4 Permanent Outage of VSC 3 247\u003c\/p\u003e \u003cp\u003e12 Model Based Voltage\/Reactive Control in Sustainable Distribution Systems 251\u003c\/p\u003e \u003cp\u003eHoan Van Pham and Sultan Nasiruddin Ahmed\u003c\/p\u003e \u003cp\u003e12.1 Introduction 251\u003c\/p\u003e \u003cp\u003e12.2 BackgroundTheory 252\u003c\/p\u003e \u003cp\u003e12.2.1 Voltage Control 252\u003c\/p\u003e \u003cp\u003e12.2.2 Model Predictive Control 253\u003c\/p\u003e \u003cp\u003e12.2.3 Model Analysis 255\u003c\/p\u003e \u003cp\u003e12.2.4 Implementation 257\u003c\/p\u003e \u003cp\u003e12.3 MPC Based Voltage\/Reactive Controller – an Example 258\u003c\/p\u003e \u003cp\u003e12.3.1 Control Scheme 258\u003c\/p\u003e \u003cp\u003e12.3.2 Overall Objective Function of the MPC Based Controller 259\u003c\/p\u003e \u003cp\u003e12.3.3 Implementation of the MPC Based Controller 261\u003c\/p\u003e \u003cp\u003e12.4 Test Results 262\u003c\/p\u003e \u003cp\u003e12.4.1 Test System and Measurement Deployment 262\u003c\/p\u003e \u003cp\u003e12.4.2 Parameter Setup and Algorithm Selection for the Controller 263\u003c\/p\u003e \u003cp\u003e12.4.3 Results and Discussion 263\u003c\/p\u003e \u003cp\u003e12.5 Conclusions 266\u003c\/p\u003e \u003cp\u003e13 Multi-Agent based Approach for Intelligent Control of Reactive Power Injection in Transmission Systems 269\u003c\/p\u003e \u003cp\u003eHoan Van Pham and Sultan Nasiruddin Ahmed\u003c\/p\u003e \u003cp\u003e13.1 Introduction 269\u003c\/p\u003e \u003cp\u003e13.2 System Model and Problem Formulation 270\u003c\/p\u003e \u003cp\u003e13.3 Multi-Agent Based Approach 275\u003c\/p\u003e \u003cp\u003e13.3.1 Augmented Lagrange Formulation 275\u003c\/p\u003e \u003cp\u003e13.3.2 Implementation Algorithm 275\u003c\/p\u003e \u003cp\u003e13.4 Case Studies and Simulation Results 277\u003c\/p\u003e \u003cp\u003e13.4.1 Case Studies 277\u003c\/p\u003e \u003cp\u003e13.4.2 Simulation Results 277\u003c\/p\u003e \u003cp\u003e14 Operation of Distribution SystemsWithin Secure Limits Using Real-Time Model Predictive Control 283\u003c\/p\u003e \u003cp\u003eHamid Soleimani Bidgoli, Gustavo Valverde, Petros Aristidou, Mevludin Glavic, and Thierry Van Cutsem\u003c\/p\u003e \u003cp\u003e14.1 Introduction 283\u003c\/p\u003e \u003cp\u003e14.2 Basic MPC Principles 285\u003c\/p\u003e \u003cp\u003e14.3 Control Problem Formulation 285\u003c\/p\u003e \u003cp\u003e14.4 Voltage CorrectionWith Minimum Control Effort 288\u003c\/p\u003e \u003cp\u003e14.4.1 Inclusion of LTC Actions as Known Disturbances 289\u003c\/p\u003e \u003cp\u003e14.4.2 Problem Formulation 290\u003c\/p\u003e \u003cp\u003e14.5 Correction of Voltages and Congestion Management with Minimum Deviation from References 291\u003c\/p\u003e \u003cp\u003e14.5.4 Problem Formulation 295\u003c\/p\u003e \u003cp\u003e14.6 Test System 296\u003c\/p\u003e \u003cp\u003e14.7 Simulation Results: Voltage Correction with Minimal Control Effort 298\u003c\/p\u003e \u003cp\u003e14.8 Simulation Results: Voltage and\/or Congestion Corrections with Minimum Deviation from Reference 302\u003c\/p\u003e \u003cp\u003e15 Enhancement of Transmission System Voltage Stability through Local Control of Distribution Networks 311\u003c\/p\u003e \u003cp\u003eGustavo Valverde, Petros Aristidou, and Thierry Van Cutsem\u003c\/p\u003e \u003cp\u003e15.1 Introduction 311\u003c\/p\u003e \u003cp\u003e15.2 Long-Term Voltage Stability 313\u003c\/p\u003e \u003cp\u003e15.2.1 Countermeasures 314\u003c\/p\u003e \u003cp\u003e15.3 Impact of Volt-VAR Control on Long-Term Voltage Stability 316\u003c\/p\u003e \u003cp\u003e15.3.1 Countermeasures 318\u003c\/p\u003e \u003cp\u003e15.4 Test System Description 319\u003c\/p\u003e \u003cp\u003e15.4.1 Test System 319\u003c\/p\u003e \u003cp\u003e15.4.2 VVC Algorithm 321\u003c\/p\u003e \u003cp\u003e15.4.3 Emergency Detection 322\u003c\/p\u003e \u003cp\u003e15.5 Case Studies and Simulation Results 323\u003c\/p\u003e \u003cp\u003e15.5.1 Results in Stable Scenarios 323\u003c\/p\u003e \u003cp\u003e15.5.2 Results in Unstable Scenarios 326\u003c\/p\u003e \u003cp\u003e15.5.3 Results with Emergency Support From Distribution 328\u003c\/p\u003e \u003cp\u003e16 Electric Power Network Splitting Considering Frequency Dynamics and Transmission Overloading Constraints 337\u003c\/p\u003e \u003cp\u003eNelson Granda and Delia G. Colomé\u003c\/p\u003e \u003cp\u003e16.1 Introduction 337\u003c\/p\u003e \u003cp\u003e16.1.1 Stage One: Vulnerability Assessment 337\u003c\/p\u003e \u003cp\u003e16.1.2 Stage Two: Islanding Process 338\u003c\/p\u003e \u003cp\u003e16.2 Network Splitting Mechanism 340\u003c\/p\u003e \u003cp\u003e16.2.1 Graph Modeling, Update, and Reduction 341\u003c\/p\u003e \u003cp\u003e16.2.2 Graph Partitioning Procedure 342\u003c\/p\u003e \u003cp\u003e16.2.3 Load Shedding\/Generation Tripping Schemes 343\u003c\/p\u003e \u003cp\u003e16.2.4 Tie-Lines Determination 344\u003c\/p\u003e \u003cp\u003e16.3 Power Imbalance Constraint Limits 344\u003c\/p\u003e \u003cp\u003e16.3.1 Reduced Frequency ResponseModel 345\u003c\/p\u003e \u003cp\u003e16.3.2 Power Imbalance Constraint Limits Determination 347\u003c\/p\u003e \u003cp\u003e16.4 Overload Assessment and Control 348\u003c\/p\u003e \u003cp\u003e16.5 Test Results 349\u003c\/p\u003e \u003cp\u003e16.5.1 Power System Collapse 349\u003c\/p\u003e \u003cp\u003e16.5.2 Application of Proposed Methodology 351\u003c\/p\u003e \u003cp\u003e16.5.3 Performance of Proposed ACIS 354\u003c\/p\u003e \u003cp\u003e16.6 Conclusions and Recommendations 356\u003c\/p\u003e \u003cp\u003e17 High-Speed Transmission Line Protection Based on Empirical Orthogonal Functions 361\u003c\/p\u003e \u003cp\u003eRommel P. Aguilar and Fabián E. Pérez-Yauli\u003c\/p\u003e \u003cp\u003e17.1 Introduction 361\u003c\/p\u003e \u003cp\u003e17.2 Empirical Orthogonal Functions 363\u003c\/p\u003e \u003cp\u003e17.2.1 Formulation 363\u003c\/p\u003e \u003cp\u003e17.3 Applications of EOFs for Transmission Line Protection 365\u003c\/p\u003e \u003cp\u003e17.3.1 Fault Direction 366\u003c\/p\u003e \u003cp\u003e17.3.2 Fault Classification 367\u003c\/p\u003e \u003cp\u003e17.3.3 Fault Location 369\u003c\/p\u003e \u003cp\u003e17.4 Study Case 369\u003c\/p\u003e \u003cp\u003e17.4.1 Transmission Line Model and Simulation 369\u003c\/p\u003e \u003cp\u003e17.4.2 The Power System and Transmission Line 370\u003c\/p\u003e \u003cp\u003e17.4.3 Training Data 370\u003c\/p\u003e \u003cp\u003e17.4.4 Training Data Matrix 370\u003c\/p\u003e \u003cp\u003e17.4.5 Signal Conditioning 373\u003c\/p\u003e \u003cp\u003e17.4.6 Energy Patterns 373\u003c\/p\u003e \u003cp\u003e17.4.7 EOF Analysis 376\u003c\/p\u003e \u003cp\u003e17.4.8 Evaluation of the Protection Scheme 379\u003c\/p\u003e \u003cp\u003e17.4.9 Fault Classification 380\u003c\/p\u003e \u003cp\u003e17.4.10 Fault Location 382\u003c\/p\u003e \u003cp\u003e17.5 Conclusions 383\u003c\/p\u003e \u003cp\u003eStudy Cases:WECC 9-bus, ATPDrawModels and Parameters 384\u003c\/p\u003e \u003cp\u003e18 Implementation of a Real Phasor Based Vulnerability Assessment and Control Scheme: The Ecuadorian WAMPAC System 389\u003c\/p\u003e \u003cp\u003ePablo X. Verdugo, Jaime C. Cepeda, Aharon B. De La Torre, and Diego E. Echeverría\u003c\/p\u003e \u003cp\u003e18.1 Introduction 389\u003c\/p\u003e \u003cp\u003e18.2 PMU Location in the Ecuadorian SNI 390\u003c\/p\u003e \u003cp\u003e18.3 Steady-State Angle Stability 391\u003c\/p\u003e \u003cp\u003e18.4 Steady-State Voltage Stability 395\u003c\/p\u003e \u003cp\u003e18.5 Oscillatory Stability 398\u003c\/p\u003e \u003cp\u003e18.5.1 Power System Stabilizer Tuning 402\u003c\/p\u003e \u003cp\u003e18.6 Ecuadorian Special Protection Scheme (SPS) 407\u003c\/p\u003e \u003cp\u003e18.6.1 SPS Operation Analysis 409\u003c\/p\u003e \u003cp\u003e18.7 Concluding Remarks 410\u003c\/p\u003e \u003cp\u003eIndex 413\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":48866389459287,"sku":"9781119214953","price":115.16,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119214953.jpg?v=1722278420","url":"https:\/\/bookcurl.com\/products\/dynamic-vulnerability-assessment-and-intelligent-control-9781119214953","provider":"Book Curl","version":"1.0","type":"link"}