A guide to the role of static state estimation in the mitigation of potential system failures
With contributions from a noted panel of experts on the topic, Advances in Electric Power and Energy: Static State Estimation 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.
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. Advances in Electric Power and Energy reviews the most recent developments in the field and:
* Offers an introduction to the topic to help non-experts (and professionals) get up-to-date on static state estimation
* Covers the essential information needed to understand power system state estimation written by experts on the subject
* Discusses a mathematical programming approach
Written for electric power system planners, operators, consultants, power system software developers, and academics, Advances in Electric Power and Energy is the authoritative guide to the topic with contributions from experts who review the most recent developments.

MOHAMED E. EL-HAWARY, PHD, 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 Principles of Electric Machines with Power Electronic Applications, Second Edition, and Electrical Power Systems: Design and Analysis.

About the Editor xi

About the Contributors xiii

Chapter 1 General Considerations 1

1.1 Prelude 1

1.2 Defining SSE 2

1.3 The Need for State Estimation 3

1.4 Static State Estimation in Practice 4

1.5 Applications That Use SE Solution 10

1.6 Overview of Chapters 13

Chapter 2 State Estimation In Power Systems Based On A Mathematical Programming Approach 23

2.1 Introduction 23

2.2 Formulation 24

2.3 Classical State Estimation Procedure 26

2.4 Mathematical Programming Solution 31

2.5 Alternative State Estimators 32

Part 1 System Failure Mitigation 59

Chapter 3 System Stress and Cascading Blackouts 61

3.1 Introduction 61

3.2 Cascading Blackouts and Previous Work 62

3.3 Problem Statement and Approach 66

3.4 DFAXes, Vulnerability, and Criticality Metrics 70

3.5 Validity of Metrics 78

3.6 Studies with Metrics 82

3.7 Summary 93

3.8 Application of Stress Metrics 94

3.9 Conclusions 94

Chapter 4 Model-Based Anomaly Detection For Power System State Estimation 99

4.1 Introduction 99

4.2 Cyberattacks on State Estimation 100

4.3 ATTACK-RESILIENT State Estimation 103

4.4 Model-Based Anomaly Detection 106

4.5 Conclusions 117

Chapter 5 Protection, Control, and Operation of Microgrids 123

5.1 Prelude 123

5.2 Introduction 126

5.3 State of the Art in Microgrid Protection and Control 128

5.4 Emerging Technologies 146

5.5 Test Case for DDSE 154

5.6 Test Results 159

5.7 Test Case for Adaptive Setting-Less Protection 161

5.8 Conclusions 167

Part 2 Robust State Estimation 171

Chapter 6 PSSE Redux: Convex Relaxation, Decentralized, Robust, And Dynamic Solvers 173

6.1 Introduction 173

6.2 Power Grid Modeling 174

6.3 Problem Statement 176

6.4 Distributed Solvers 186

6.5 Robust Estimators and Cyberattacks 193

6.6 Power System State Tracking 198

6.7 Discussion 202

Chapter 7 Robust Wide-Area Fault Visibility and Structural Observability In Power Systems With Synchronized Measurement Units 209

7.1 Introduction 209

7.2 Robust Fault Visibility Using Strategically Deployed Synchronized Measurements 210

7.3 Optimal PMU Deployment for System-Wide Structural Observability 221

7.4 Conclusions 229

Chapter 8 A Robust Hybrid Power System State Estimator With Unknown Measurement Noise 231

8.1 Introduction 231

8.2 Problem Statement 233

8.3 Proposed Framework for Robust Hybrid State Estimation 234

8.4 Numerical Results 245

8.5 Conclusions 249

Chapter 9 Least-Trimmed-Absolute-Value State Estimator 255

9.1 Bad Data Detection and Robust Estimators 256

9.2 Results and Discussion 266

9.3 Conclusions 287

Part 3 State Estimation For Distribution Systems 295

Chapter 10 Probabilistic State Estimation In Distribution Networks 297

10.1 Introduction 297

10.2 State Estimation in Distribution Networks 298

10.3 Improving Observability in Distribution Networks 309

10.4 Conclusion 324

Chapter 11 Advanced Distribution System State Estimation In Multi-Area Architectures 329

11.1 Issues and Challenges of Distribution System State Estimation 329

11.2 Distribution System Multi-Area State Estimation (DS-MASE) Approach 342

11.3 Application of the DS-MASE Approach 357

11.4 Validity and Applicability of DS-MASE Approach 369

Part 4 Parallel/Distributed Processing 375

Chapter 12 Hierarchical Multi-Area State Estimation 377

12.1 Introduction 377

12.2 Preliminaries 381

12.3 Modeling and Problem Formulation 385

12.4 A Brief Survey of Solution Techniques 387

12.5 Hierarchical State Estimator Via Sensitivity Function Exchanges 393

12.6 Add-On Functions in Multi-area State Estimation 399

12.7 Properties 401

12.8 Simulations 405

12.9 Conclusions 409

Chapter 13 Parallel Domain-Decomposition-Based Distributed State Estimation For Large-Scale Power Systems 413

13.1 Introduction 413

13.2 Fundamental Theory and Formulation 416

13.3 Experimental Results 436

13.4 Conclusion 449

Chapter 14 Dishonest Gauss-Newton Method-Based Power System State Estimation On A GPU 455

14.1 Introduction 455

14.2 Background 456

14.3 Performance of Dishonest Gauss-Newton Method 461

14.4 GPU Implementation 463

14.5 Simulation Results 467

14.6 Discussions on Scalability 468

14.7 Distributed Method of Parallelization 470

14.8 Conclusions 473

Index 475