Craig Rieger, PhD, is Chief Control Systems Research Engineer at the Idaho National Laboratory. His research focus is on next generation resilient control systems.Ronald Boring, PhD, is Researcher and Principal Investigator at Idaho National Laboratory. His primary research foci are on human reliability, human factors, and human-computer interaction forums. Brian Johnson, PhD, is University Distinguished Professor and Schweitzer Engineering Laboratories Endowed Chair in Power Engineering in the Department of Electrical and Computer Engineering at the University of Idaho. Timothy McJunkin is an Electrical Engineer at the Idaho National Laboratory. His primary research foci are on the development of interest resilient control of critical infrastructure, Smart Grid for renewable energy integration, and design of zero carbon microgrids.

• Foreword xvPreface xviiAcknowledgments xxiiiEditors Biography xxvList of Contributors xxviiPart I Introduction 11 Basis, Definition, and Application 3Craig Rieger1.1 Introduction 31.2 Definition and Application 3References 62 General Use Case Introduction 7Brian Johnson2.1 Introduction 72.2 Importance of Resilient Controls for Power Systems 72.3 Power Systems Operations and Control 72.4 Summary 9References 9Part II Infrastructure Fundamentals 113 Power Grid Architecture 13Brian Johnson and Rômulo BainyObjectives 133.1 Introduction 133.2 Classical Power System Architectures 143.3 Emerging Architecture Trends 173.3.1 Smart Grids 173.3.2 Microgrids 203.4 Power Systems Operations and Control 223.5 Power Systems Planning 243.5.1 Modeling and Simulation 253.6 Measures of Performance 263.7 Summary 29Further Reading 30References 314 Control System Architecture 33Thomas BaldwinObjectives 334.1 Introduction 334.1.1 Background 334.1.2 Basic Generator Control Loops 344.1.3 Load Frequency Control 354.1.4 The Generator 354.1.5 The Load 364.1.6 The Turbine-Based Prime Mover 374.1.7 The Speed Governor 384.1.8 The Load Frequency Control Loop 394.1.9 Multiple Generators Operating with LFC 404.2 Automatic Generation Control 424.2.1 Background 424.2.2 The AGC in Single Area Systems 424.2.3 The AGC in Multi-Area Systems 434.2.4 The Tie Line 434.2.5 Tie Line Control 474.2.6 AGC with Generation Allocation 474.3 Reactive Power and Voltage Control 494.3.1 Background 494.3.2 Voltage Sensor 514.3.3 Amplifier 514.3.4 Exciter 514.3.5 Generator 514.3.6 The Voltage Control Loop 524.4 Excitation System Stabilizer 524.4.1 Rate Feedback Method 524.4.2 PID Controller 544.5 Summary 55Further Reading 565 Communication Architecture 57Chris DyerObjectives 575.1 Introduction 575.2 Communication Media 585.2.1 Copper Wire 595.2.1.1 Telecommunication Industry Association (TIA)/Electronic Industries Association (EIA) RS- 232 595.2.1.2 Twisted Pair (TIA RS-485) 595.2.1.3 Twisted Pair (Ethernet [10Base-T]) 605.2.2 Fiber-Optic Cable 605.2.2.1 Optical Ground Wire (OPGW) 615.2.2.2 All-Dielectric Self-Supporting (ADSS) Cables 625.2.2.3 Underground Cables 625.2.2.4 Splice Box 635.2.2.5 Fiber-optic Terminations 635.2.3 Patch Panel 655.2.3.1 Patch Cables 655.2.3.2 Fiber-optic Loss Calculations 665.2.4 Radio-Frequency (RF) Communications 665.2.4.1 Microwave 665.2.4.2 VHF/UHF Radio 685.2.4.3 Spread-Spectrum Communication 685.2.4.4 Mesh Communication Networks 685.2.4.5 Radio Propagation and Path Studies 685.2.5 Local Area Networks 685.2.5.1 Business Enterprise Networks 695.2.5.2 Operational Enterprise Networks 695.2.5.3 Remote Outstation Networks 735.2.6 Backhaul Communications 785.2.7 Emerging Technologies and Other Considerations 795.3 Summary 80References 81Part III Disciplinary Fundamentals 836 Introducing Interdisciplinary Studies 85Craig RiegerObjectives 856.1 Introduction 856.2 The Pathway to an Interdisciplinary Team 86Further Reading 877 Cybersecurity 89Daniel Conte de Leon, Georgios M. Makrakis, and Constantinos KoliasObjectives 897.1 Introduction 897.2 Systems and Control Systems 907.2.1 Systems, Subsystems, and Analysis Boundaries 907.2.2 System Subjects and Objects 907.2.3 Subject Communication and Cyber Systems 907.3 Fundamental Cybersecurity Objectives: The CIA Triad 917.3.1 Confidentiality 917.3.2 Integrity 927.3.3 Availability 937.4 Fundamental Cybersecurity Techniques 937.4.1 Cryptography 937.4.1.1 Symmetric Encryption 947.4.1.2 Asymmetric Encryption 947.4.1.3 Digital Signatures 957.4.2 Authentication and Identity 957.4.3 Authorization and Access Control 967.4.4 Accountability 977.4.5 Redundancy and Replication 977.5 Threats, Vulnerabilities, and Attacks 977.5.1 Definitions 977.5.2 Common Types of ICS Vulnerabilities 987.5.2.1 Human Related 987.5.2.2 Software or Firmware Based 997.5.2.3 Policies and Procedures 997.5.3 Attack Stages and the Cyber Kill Chain 1007.5.3.1 Reconnaissance 1007.5.3.2 Weaponization 1007.5.3.3 Delivery 1017.5.3.4 Exploitation 1017.5.3.5 Installation 1017.5.3.6 Command and Control 1017.5.3.7 Actions on Objectives 1017.5.3.8 ICS Cyber Kill Chain 1017.6 Secure System Design Principles 1027.6.1 Continuous Improvement 1027.6.2 Defense in Depth 1027.6.3 Least Privilege 1037.6.4 Validated Design and Implementation 1037.6.5 Fail-safe Defaults 1037.6.6 Separation of Duties 1047.6.7 Psychological Acceptability 1047.6.8 Modularization 1047.6.9 Accountability 1047.7 Approaches for Threat and Risk Assessment and Mitigation 1057.7.1 Risk Framing, Legal, and Compliance 1057.7.2 Risk Assessment 1067.7.3 Risk Response or Treatment 1067.7.4 Risk Monitoring 1067.7.5 Security Management and Continuous Improvement 1077.8 Approaches for Incident Detection and Response 1077.8.1 Incident and Intrusion Detection 1077.8.1.1 Host-Based IDS 1087.8.1.2 Network-Based IDS 1087.8.1.3 Distributed or Hybrid IDS 1087.8.1.4 Signature Detection 1087.8.1.5 Anomaly Detection 1087.8.2 Incident Response 1097.9 Summary 1097.10 Thoughtful Questions to Ensure Comprehension 109Further Reading 110References 1108 Control Theory 113Desineni S. NaiduObjectives 1138.1 Introduction 1138.1.1 Formal Statement of Optimal Control Problem 1148.2 Deterministic Linear Systems 1148.2.1 Open-Loop Optimal Control of Linear Systems 1148.2.2 Closed-Loop Optimal Control of Linear Systems 1158.2.3 Finite-Time Linear Quadratic Regulator: Time-Varying Case 1168.2.4 Infinite-Interval Regulator System: Time-Invariant Case 1168.2.5 Linear Quadratic Tracking System: Finite-Time Case 1178.2.6 Gain Margin and Phase Margin 1188.2.7 Gain Margin 1188.2.8 Phase Margin 1188.3 Pontryagin Principle and HJB Equation 1198.3.1 The Hamilton–Jacobi–Bellman (HJB) Equation 1198.4 Stochastic Linear Systems 1208.4.1 Optimal Estimation 1208.4.2 Optimal Control 1218.5 Deterministic Nonlinear Systems 1218.5.1 Finite-Horizon Regulation and Tracking for Nonlinear Systems 1228.5.2 Finite-Horizon Regulator 1228.5.3 Finite-Horizon Tracking for Nonlinear Systems 1238.6 Summary 1248.7 Thoughtful Questions to Ensure Comprehension 124Further Reading 125References 1259 Human System Interfaces 127Ronald BoringObjectives 1279.1 Introduction 1279.1.1 Control Systems 1279.1.2 History of Humans and Control Systems 1289.1.3 Common Elements of Control System HSIs 1289.1.4 Consequences of Poor HSIs in Control Systems 1299.2 Basic Methods 1319.2.1 Introduction to User-Centered Design 1319.2.2 Design Planning 1339.2.3 Prototyping Process 1349.2.4 Evaluation Process 1359.2.5 Validation versus Verification 1389.3 Summary 140Further Reading 142References 142Part IV Metrics Fundamentals 14510 Differentiating Resilience 147Jeffrey D. TaftObjectives 14710.1 Introduction 14710.2 Conventional Views of Grid Resilience 15010.3 Grid Characteristics 15110.4 Grid Resilience and the Relationship to Electric Reliability 15210.5 Characterization of Resilience 15510.5.1 Stress and Stressors 15610.5.2 Physical Scale 15610.5.3 Temporal Scale 15710.5.4 Strain 15710.5.5 Resilience Domains 15710.5.5.1 Stress Avoidance 15710.5.5.2 Stress Resistance 15810.5.5.3 Strain Adjustment 15910.5.6 Foundational Support 16010.6 Architectural Principles and Concepts for Resilience 16010.6.1 All Hazards Approach 16210.6.2 Situational Awareness 16210.6.3 ULS Normal Failures Approach 16210.6.4 System Hardness 16210.6.5 Flexibility 16210.6.6 Extensibility 16310.6.7 Agility 16310.6.8 Distributed Versus Centralized Systems 16310.6.9 Buffering 16310.6.10 Structural Resilience 16310.6.11 Redundancy 16410.7 Structural Resilience Quantification and Valuation 16410.8 Summary 166Further Reading 167References 16711 Cross-architecture Metrics 169Timothy McJunkinObjectives 16911.1 Definition of Resilience 16911.2 Notional Capture of Resilience Adaptive Capacity 17311.3 Response Epoch: Adaptive Capacity on an Asset-Level Development 17411.4 Adaptive Capacity on an Aggregated-Level Development 176Exercises 178Exercises 17811.5 Cybersecurity Considerations 17911.6 Consideration of Resist Epoch (Inertia) 18211.7 Consideration of Recover and Restore Epochs 183References 184Part V Resilience Application 18512 Introducing the Grid Game 187Timothy McJunkinObjectives 18712.1 Introduction 18712.2 Download/Install the Game 18712.3 Play the Grid Game 18812.4 Fundamentals 19412.5 Evaluate the Grid Game and Players (Yourself and Others) 19612.6 Play Together 19812.7 Improve the Game 198References 19813 Cybersecurity and Resilience for the Power Grid 201xi Qin, Kelvin Mai, Neil Ortiz, Keerthi Koneru, and Alvaro A. CardenasObjectives 20113.1 Introduction 20113.2 Operation Technologies in the Power Grid 20113.3 Cyberattacks to the Power Grid 20613.3.1 Attacks in Ukraine 20613.3.2 Other Potential Attacks 20813.4 Research Efforts 20813.4.1 Classical Power Grid Systems 20813.4.2 Smart Grid Systems 20913.4.3 Grid Simulator 21113.5 Summary 21113.6 Thoughtful Questions to Ensure Comprehension 211Further Reading 212References 21214 Control Challenges 215Quanyan ZhuObjectives 21514.1 Introduction 21514.2 Resiliency Challenges in Control Systems 21614.3 Resiliency Design Framework 21714.3.1 Control of Autonomous Systems in Adversarial Environment 21814.3.2 Cross-Layer Defense for Cloud-Enabled Internet of Controlled Things 21914.4 Resiliency for Decentralized Control Systems 22114.5 Summary 22314.6 Thoughtful Questions to Ensure Comprehension 223Further Reading 224References 22515 Human Challenges 231Anshul RegeObjectives 23115.1 Introduction 23115.2 Experiential Learning and the Multidisciplinary Grid Game 23215.2.1 Grid Game Case Study 23215.2.2 Grid Operations and Cybersecurity 23315.2.2.1 Grid Operations 23315.2.2.2 Microgrid Stability and Generation Control System 23315.2.2.3 Generator Inertia 23315.2.2.4 Energy Storage 23415.2.3 Cyber Adversarial Decision-Making 23415.2.4 Cyber Defender Decision-Making 23615.2.4.1 Group Dynamics and Divisions of Labor 23615.2.4.2 Cybersecurity Preparations 23615.2.4.3 Response to Cyberattacks 23715.2.5 Cyber-Field Research 23715.2.5.1 Designing and Conducting Research 23715.2.5.2 Weaving Multiple Methods in Real Time 23715.2.5.3 Exposure to All Phases of Research 23815.3 Benefits of Gamifying Cybersecurity 23915.3.1 Discipline-Specific Benefits 23915.3.2 Challenges 23915.4 Summary 239Further Reading 241References 241Part VI Additional Design Considerations 24316 Interdependency Analysis 245Ryan HruskaObjectives 24516.1 Introduction 24516.1.1 Dependencies and Interdependencies 24516.1.2 Electric-Grid System Dependencies 24616.2 Approaches to Infrastructure Dependency Analysis 24716.2.1 Engineering Models 24716.2.2 Systems Engineering 24816.2.3 Geospatial Modeling 24816.2.4 All-Hazards Analysis 24916.3 Bulk Power Systems Interdependency Case Studies 24916.3.1 Natural Gas Expansion 24916.3.1.1 Natural Gas Interdependencies for Electric Generation 25116.3.1.2 Seasonal Impacts 25216.3.2 Water Interdependencies 25316.4 Summary 256Further Reading 256References 25717 Multi-agent Control Systems 259Craig RiegerObjectives 25917.1 Introduction 25917.1.1 What Is an Agent? 25917.1.2 Intelligent Agent 25917.1.3 Resilient Agent 26017.1.4 Multi-agents and Benefit to Resilience 26017.2 Control System Design 26117.2.1 Tiers of Control 26117.2.2 Decomposition of Operational Philosophy into Management and Coordination Layers 26117.2.3 Decomposition of Operational Philosophy into Execution Layer 26317.2.4 Data-driven Methodology for Application of Tiered Control 26417.2.5 Cyber–Physical Degradation Assessment 26417.3 Control System Application 26717.3.1 Human Decision Integration into Management and Execution Layers 26717.3.2 Distributed Control and the Execution Layer Formulation 26817.3.3 Domain Application 26917.4 Summary 272Further Reading 273An overview of a HMADS for power system applications: 273References 27318 Other Examples of Resilience Application 275Meghan G. Sahakian and Eric D. VugrinObjectives 27518.1 Introduction 27518.2 Resilient Design Capacities 27618.3 Anticipative Capacity 27618.4 Absorptive Capacity 27718.5 Adaptive Capacity 27818.6 Restorative Capacity 27918.7 Considerations for Resilient Design 27918.8 System of Interest 28018.9 Threat Space 28118.10 Operational Constraints 28218.11 Summary 282Further Reading 283References 283Part VII Conclusions 28519 Summary and Challenge for the Future 287Craig Rieger19.1 Introduction 28719.2 Resilience is not a Design Layer, It is a Philosophy 28719.3 Resilience and the Road to Autonomous Systems 288References 288Index 289