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<p>About the Editor xi</p> <p>About the Contributors xiii</p> <p><b>Chapter 1 </b><b>General Considerations 1</b></p> <p>1.1 Prelude 1</p> <p>1.2 Defining SSE 2</p> <p>1.3 The Need for State Estimation 3</p> <p>1.4 Static State Estimation in Practice 4</p> <p>1.5 Applications That Use SE Solution 10</p> <p>1.6 Overview of Chapters 13</p> <p><b>Chapter 2 </b><b>State Estimation In Power Systems Based On A Mathematical Programming Approach 23</b></p> <p>2.1 Introduction 23</p> <p>2.2 Formulation 24</p> <p>2.3 Classical State Estimation Procedure 26</p> <p>2.4 Mathematical Programming Solution 31</p> <p>2.5 Alternative State Estimators 32</p> <p><b>Part 1 System Failure Mitigation 59</b></p> <p><b>Chapter 3 </b><b>System Stress and Cascading Blackouts 61</b></p> <p>3.1 Introduction 61</p> <p>3.2 Cascading Blackouts and Previous Work 62</p> <p>3.3 Problem Statement and Approach 66</p> <p>3.4 DFAXes, Vulnerability, and Criticality Metrics 70</p> <p>3.5 Validity of Metrics 78</p> <p>3.6 Studies with Metrics 82</p> <p>3.7 Summary 93</p> <p>3.8 Application of Stress Metrics 94</p> <p>3.9 Conclusions 94</p> <p><b>Chapter 4 </b><b>Model-Based Anomaly Detection For Power System State Estimation 99</b></p> <p>4.1 Introduction 99</p> <p>4.2 Cyberattacks on State Estimation 100</p> <p>4.3 ATTACK-RESILIENT State Estimation 103</p> <p>4.4 Model-Based Anomaly Detection 106</p> <p>4.5 Conclusions 117</p> <p><b>Chapter 5 </b><b>Protection, Control, and Operation of Microgrids 123</b></p> <p>5.1 Prelude 123</p> <p>5.2 Introduction 126</p> <p>5.3 State of the Art in Microgrid Protection and Control 128</p> <p>5.4 Emerging Technologies 146</p> <p>5.5 Test Case for DDSE 154</p> <p>5.6 Test Results 159</p> <p>5.7 Test Case for Adaptive Setting-Less Protection 161</p> <p>5.8 Conclusions 167</p> <p><b>Part 2 Robust State Estimation 171</b></p> <p><b>Chapter 6 </b><b>PSSE Redux: Convex Relaxation, Decentralized, Robust, And Dynamic Solvers 173</b></p> <p>6.1 Introduction 173</p> <p>6.2 Power Grid Modeling 174</p> <p>6.3 Problem Statement 176</p> <p>6.4 Distributed Solvers 186</p> <p>6.5 Robust Estimators and Cyberattacks 193</p> <p>6.6 Power System State Tracking 198</p> <p>6.7 Discussion 202</p> <p><b>Chapter 7 </b><b>Robust Wide-Area Fault Visibility and Structural Observability In Power Systems With Synchronized Measurement Units 209</b></p> <p>7.1 Introduction 209</p> <p>7.2 Robust Fault Visibility Using Strategically Deployed Synchronized Measurements 210</p> <p>7.3 Optimal PMU Deployment for System-Wide Structural Observability 221</p> <p>7.4 Conclusions 229</p> <p><b>Chapter 8 </b><b>A Robust Hybrid Power System State Estimator With Unknown Measurement Noise 231</b></p> <p>8.1 Introduction 231</p> <p>8.2 Problem Statement 233</p> <p>8.3 Proposed Framework for Robust Hybrid State Estimation 234</p> <p>8.4 Numerical Results 245</p> <p>8.5 Conclusions 249</p> <p><b>Chapter 9 </b><b>Least-Trimmed-Absolute-Value State Estimator 255</b></p> <p>9.1 Bad Data Detection and Robust Estimators 256</p> <p>9.2 Results and Discussion 266</p> <p>9.3 Conclusions 287</p> <p><b>Part 3 State Estimation For Distribution Systems 295</b></p> <p><b>Chapter 10 </b><b>Probabilistic State Estimation In Distribution Networks 297</b></p> <p>10.1 Introduction 297</p> <p>10.2 State Estimation in Distribution Networks 298</p> <p>10.3 Improving Observability in Distribution Networks 309</p> <p>10.4 Conclusion 324</p> <p><b>Chapter 11 </b><b>Advanced Distribution System State Estimation In Multi-Area Architectures 329</b></p> <p>11.1 Issues and Challenges of Distribution System State Estimation 329</p> <p>11.2 Distribution System Multi-Area State Estimation (DS-MASE) Approach 342</p> <p>11.3 Application of the DS-MASE Approach 357</p> <p>11.4 Validity and Applicability of DS-MASE Approach 369</p> <p><b>Part 4 Parallel/Distributed Processing 375</b></p> <p><b>Chapter 12 </b><b>Hierarchical Multi-Area State Estimation 377</b></p> <p>12.1 Introduction 377</p> <p>12.2 Preliminaries 381</p> <p>12.3 Modeling and Problem Formulation 385</p> <p>12.4 A Brief Survey of Solution Techniques 387</p> <p>12.5 Hierarchical State Estimator Via Sensitivity Function Exchanges 393</p> <p>12.6 Add-On Functions in Multi-area State Estimation 399</p> <p>12.7 Properties 401</p> <p>12.8 Simulations 405</p> <p>12.9 Conclusions 409</p> <p><b>Chapter 13 </b><b>Parallel Domain-Decomposition-Based Distributed State Estimation For Large-Scale Power Systems 413</b></p> <p>13.1 Introduction 413</p> <p>13.2 Fundamental Theory and Formulation 416</p> <p>13.3 Experimental Results 436</p> <p>13.4 Conclusion 449</p> <p><b>Chapter 14 </b><b>Dishonest Gauss–Newton Method-Based Power System State Estimation On A GPU 455</b></p> <p>14.1 Introduction 455</p> <p>14.2 Background 456</p> <p>14.3 Performance of Dishonest Gauss–Newton Method 461</p> <p>14.4 GPU Implementation 463</p> <p>14.5 Simulation Results 467</p> <p>14.6 Discussions on Scalability 468</p> <p>14.7 Distributed Method of Parallelization 470</p> <p>14.8 Conclusions 473</p> <p>Index 475</p>

<p><b>MOHAMED E. EL-HAWARY, P<small>H</small>D, </b>is Professor of Electrical and Computer Engineering at Dalhousie University. He is also the Editor for the IEEE Press Power Engineering Series. He has published multiple books with Wiley-IEEE Press, including <i>Principles of Electric Machines with Power Electronic Applications, Second Edition, </i>and<i> Electrical Power Systems: Design and Analysis.</i></p>

<p><b>A guide to the role of static state estimation in the mitigation of potential system failures</b> <p>With contributions from a noted panel of experts on the topic, <i>Advances in Electric Power and Energy: Static State Estimation</i> addresses the wide-range of issues concerning static state estimation as a main energy control function and major tool for evaluating prevailing operating conditions in electric power systems worldwide. <p>This book is an essential guide for system operators who must be fully aware of potential threats to the integrity of their own and neighboring systems. The contributors provide an overview of the topic and review common threats such as???cascading black-outs to model-based anomaly detection to the operation of micro-grids and much more. The book also includes a discussion of an effective mathematical programming approach to state estimation in power systems. <i>Advances in Electric Power and Energy</i> reviews the most recent developments in the field and: <ul> <li>Offers an introduction to the topic to help non-experts (and professionals) get up-to-date on static state estimation</li> <li>Covers the essential information needed to understand power system state estimation written by experts on the subject</li> <li>Discusses a mathematical programming approach</li> </ul> <p>Written for electric power system planners, operators, consultants, power system software developers, and academics, <i>Advances in Electric Power and Energy</i> is the authoritative guide to the topic with contributions from experts who review the most recent developments.

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