Cyberphysical Infrastructures in Power Systems: Architectures and Vulnerabilities

Front Cover
Cyberphysical Infrastructures in Power Systems
Copyright
Contents
About the authors
Preface
Acknowledgments
Part 1 Background
1 Overview
1.1 Cyberphysical security modeling systems (CPS)
1.1.1 Introduction
1.1.2 Wide-area monitoring, protection and control systems
1.1.3 Wide-area protection
1.1.4 Phasor measurement units
1.2 Cyberattack taxonomy
1.2.1 Cyberattack classification
1.2.2 Coordinated attacks on WAMPAC
1.2.3 Cyberphysical security using game-theoretic approach
1.2.4 Cyberlayer risk assessment
1.2.5 Attack modeling
1.2.6 Game formulation and solution strategies
1.3 Challenges in cyberphysical power systems
1.3.1 Signal sampling
1.3.2 Signal quantization
1.3.3 Communication delay
1.3.4 Packet dropouts
1.3.5 Medium access constraints
1.3.6 Channel fading
1.3.6.1 Information-theory based approach
1.3.6.2 Stochastic system approach
1.3.7 Power constraints
1.3.7.1 Reducing the transmission rate
Deterministic case
Stochastic case
Event-based case
1.3.7.2 Packet size reduction
Deterministic case
Stochastic case
1.4 Secure industrial control systems
1.4.1 Introduction
1.4.2 Progress of SICS
1.4.3 Major security objectives
1.5 Game-theoretic methods
1.5.1 Robustness issue
1.5.2 Resilient control design
1.5.3 Hierarchical systems
1.5.4 Physical layer control system problem
1.6 Notes
References
2 Smart grids: control and cybersecurity
2.1 A view of networked microgrids
2.1.1 Introduction
2.1.2 Types of networked microgrids
2.1.3 Star-connected NMG
2.1.4 Ring-connected NMG
2.1.5 Mesh-connected NMG
2.1.6 Control approaches in NMGs
2.2 Cyberattack protection and control of microgrids
2.2.1 Model of microgrid system
2.2.2 Observation model and cyberattack
2.2.3 Cyberattack minimization in smart grids
2.2.4 Stabilizing feedback controller
2.2.5 Simulation results I
2.3 Smart grid cybersecurity analysis
2.3.1 Introduction
2.3.2 Power network model and state estimation
2.3.2.1 Unobservable data attack and security index
2.3.2.2 Measurement set robustness analysis
2.3.3 Attack construction problem
2.3.3.1 l1 relaxation problem (2.30) is a cardinality minimization problem
2.3.4 Main result
2.4 Main attributes
2.4.1 Rationale of the no injection assumption
2.4.2 Relationship with minimum cut based results
2.4.3 Relationship with compressed sensing results
2.4.4 Definitions
2.4.5 The equivalence between two relations
2.4.6 Proof of proposition
2.4.7 Simulation results II
2.5 Two-area power system
2.5.1 Introduction
2.5.2 Simulation results III
2.6 Notes
References
Part 2 Control, estimation, and fault detection
3 Safe control methods
3.1 Introduction
3.2 State feedback controller
3.2.1 Threat model
3.2.2 Design of the state feedback controller
3.3 Observer-based controller
3.3.1 Design of a state feedback controller
3.3.2 Simulation results
3.4 Performance-degradation issues
3.4.1 Preliminaries
3.4.2 System description
3.4.3 X2 failure detector
3.4.4 Threat model
3.4.5 Recursive version of Rk
3.4.6 Ellipsoidal approximation of Rk
3.4.7 Simulation results
3.5 Decentralized secure control
3.5.1 Problem statement
3.5.2 Design results
3.5.3 Application to a four-area power system
3.6 Notes
References
4 Event-triggering control of cyberphysical power systems
4.1 Introduction
4.2 Problem formulation and the control scheme
4.2.1 The event triggering mechanism
4.2.2 The attack model
4.2.3 The observer-based control scheme
4.3 Design results
4.4 Illustrative examples
4.4.1 Two-area power systems
4.4.2 A single machine connected to an infinite-bus
4.5 Conclusions
Appendix: proof of Theorem 14
References
5 Wide-area monitoring and estimation systems
5.1 Introduction
5.2 WAMS applications and state estimation
5.2.1 Three possible states
5.2.2 Basic paradigms of state estimation
5.2.3 State representation of a power grid
5.2.4 Properties of probability vector
5.2.5 Observation model
5.2.6 Correlation of noise
5.2.7 Function of frequency oscillation state
5.2.8 Attack vector
5.3 Median regression function-based approach
5.3.1 Initial regression analysis using the mapping function
5.3.2 Additional geometric properties
5.3.3 Frequency oscillation state estimation
5.3.4 Interacting multiple model (IMM)-based fusion
5.3.5 Residual generation using error matrix
5.3.6 Residual evaluation using cross-spectral density function
5.4 Implementation and evaluation results
5.4.1 System disturbances
5.4.2 Deliberate data-injection scenarios
5.4.3 Aim of a hacker
5.4.4 Performance evaluation using regression methods
5.4.5 Estimation comparison with track fusion
5.4.6 MSE-based estimation comparison
5.5 Notes
References
Part 3 Power systems' architectures
6 Future grid architectures
6.1 Communication architectures in smart grids
6.1.1 Introduction
6.1.2 A framework of the next-generation power grid
6.1.3 Network architecture
6.1.4 Wide-area networks
6.1.5 Field-area networks
6.1.6 Home-area networks
6.1.7 Delay pattern
6.2 Wide-area monitoring control of smart grids
6.2.1 Power system dynamic model
6.2.2 Sensors and actuators
6.2.3 Control design
6.2.4 Simulation results
6.3 Wide-area case studies
6.3.1 Monitoring system case study
6.3.2 Monitoring and control systems case study
6.4 Notes
References
7 Mature industrial functions
7.1 Secure remote state estimation
7.1.1 Introduction
7.1.2 Problem formulation
7.1.2.1 System model
7.1.2.2 Plant model
7.1.2.3 The χ2 detector
7.1.2.4 Linear FDI attack
7.1.3 Secure modules for data transmission
7.1.3.1 Structure of secure modules for data transmission
7.1.3.2 Feasibility analysis
7.1.4 Detection and performance analysis in various attack scenarios
7.1.4.1 Scenario I: no information leakage
7.1.4.2 Scenario II: partial information leakage
7.1.4.3 Scenario III: information leakage
7.1.5 Extension to detect other attacks
7.1.5.1 False-data injection attack
7.1.5.2 Replay attack
7.1.6 Proofs of the lemmas and theorems
Appendix A
A.1. Proof of Lemma 6
Appendix B
Proof of Lemma 7
Appendix C
Proof of Lemma 9
Appendix D
Appendix E
7.1.7 Simulation results
7.1.7.1 Simulation result in Scenario I
7.1.7.2 Simulation result in Scenario II
7.1.7.3 Simulation result in Scenario III
7.1.7.4 Extension to detect the replay attack
7.2 Notes
References
8 Secure filtering in power systems
8.1 Introduction
8.2 Problem description
8.3 Main results
8.4 Simulation results
8.5 Notes
References
9 Basic mathematical tools
9.1 Finite-dimensional spaces
9.1.1 Vector spaces
9.1.2 Norms of vectors
Induced norms of matrices
9.1.3 Some basic topology
9.1.4 Convex sets
9.1.5 Continuous functions
9.1.6 Function norms
9.1.7 Mean value theorem
9.1.8 Implicit function theorem
9.2 Matrix theory
9.2.1 Fundamental subspaces
9.2.2 Change of basis and invariance
9.2.3 Calculus of vector-matrix functions of a scalar
9.2.4 Derivatives of vector-matrix products
9.2.5 Positive definite and positive semidefinite matrices
9.2.6 Matrix ellipsoid
9.2.7 Power of a square matrix
9.2.8 Exponential of a square matrix
9.2.9 Eigenvalues and eigenvectors of a square matrix
9.2.10 The Cayley–Hamiltonian theorem
9.2.11 Trace properties
9.2.12 Kronecker product and vec
9.2.13 Partitioned matrices
9.2.14 The matrix inversion lemma
9.2.15 Strengthened version of the lemma of Lyapunov
9.2.16 The singular value decomposition
9.3 Some bounding inequalities
9.3.1 Bounding inequality A
9.3.2 Bounding inequality B
9.3.3 Bounding inequality C
9.3.4 Bounding inequality D
9.3.5 Young's inequality
9.4 Gronwall-Bellman inequality
9.5 Schur complements
9.6 Some useful lemmas
9.7 Fundamental stability theorems
9.7.1 Lyapunov–Razumikhin theorem
9.7.2 Lyapunov–Krasovskii theorem
9.7.3 Halany theorem
9.7.4 Types of continuous Lyapunov–Krasovskii functionals
9.7.5 Some discrete Lyapunov–Krasovskii functionals
9.8 Elements of algebraic graphs
9.8.1 Graph theory
9.8.2 Undirected graph
9.8.3 Main graphs
9.8.4 Graph operations
9.8.5 Basic properties
9.8.6 Connectivity properties of digraphs
9.8.7 Properties of adjacency matrix
9.8.8 Laplacian spectrum of graphs
9.9 Linear matrix inequalities
9.9.1 Basics
9.9.2 Some standard problems
9.9.3 The S-procedure
9.10 Some formulas on matrix inverses
9.10.1 Inverse of block matrices
9.10.2 The matrix inversion lemma
9.11 Notes
References
Index
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