Other Research Areas
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Smart Grid Modeling, Analysis, Resilience and Security
Energy is a quantity that measures the ability of a physical system to produce change on another physical system. Changes are produced when the energy is transferred from one system to another through (i) physical/thermodynamical work, (ii) heat and/or (iii) mass transfer. Electricity is an energy “carrier.” Although energy is not naturally available in the form of electricity nor is electricity directly used to produce change, its conversion to and from electricity enables the transmission of power from generation to consumption over a complex interconnected grid.
The term “grid” in the context of power systems has traditionally been used to represent the network of electrical components used to supply, transmit and consume electric power. The term can refer to the complete or a suitable subset of electricity generation, transmission and distribution infrastructure. Popular grid topologies in North America are radial and mesh while loop topologies are predominant in Europe.
The power grid is a critical infrastructure. Critical infrastructures are defined as assets that are essential for the functioning of a society and economy. Common critical infrastructures include energy, telecommunications, agriculture and food, water supply, public health, transportation, and financial services. The integration of energy system with telecommunications and financial services is what is often termed the “smart grid.”
Smart Grid
A smart grid can be described as a power system having bidirectional communications and bidirectional power flow. This is facilitated in part through the use of advanced sensing the metering devices and advanced control technologies. One of the key components is improved (human) operator interface and decision support.
The North American Electrical Reliability Corporation (NERC) defines the smart grid as “the integration and application of real-time monitoring, advanced sensing, communications, analytics, and control, enabling the dynamic flow of both energy and information to accommodate existing and new forms of supply, delivery, and use in a secure, reliable, and efficient electric power system, from generation source to end-user.”
Power systems today have some form of intelligence. Therefore many describe the marriage of information technology with power systems as a smarter grid.
Why Do We Need a Smarter Grid?
It is predicted that the grid today will not be capable of powering for the world’s future energy requirements. Moreover the deregulation of the energy industry necessitates high granularity of informational, financial and physical transactions to assure adequate power system operation in a competitive electricity market. Information-enhanced operation can enable greater reliability and introduce advancement not envisioned yet. The “smartness” permits optimization for integration of bulk generation and storage and distributed resources, more reliable transmission and distribution and expanded consumer end-uses. This promotes reliability, conservation of energy, mitigation of environmental impact and lower cost.
Smart Grid and Security
While this integration of cyber technology with the power system enables new opportunities, it also creates a host of unfamiliar vulnerabilities stemming from cyber intrusion and corruption potentially leading to devastating physical effects. The security of a system is as strong as its weakest link. Thus, the scale and complexity of the smart grid, along with its increased connectivity and automation make the task of cyber protection particularly challenging.
From a technical perspective there is increased opportunity for cyber attack because of the greater dependence on intelligent electronic devices, communications and advanced metering amongst other intelligent systems. Such cyber infrastructure typically employs standardized information technologies that may have documented vulnerabilities. Coupled with increased economic motivations for attack that stem, in part, from privatization of the energy industry, cyber security of the smart grid represents a timely research and engineering problem.
Research Focus
The first step in understanding how to secure emerging systems such as the smart grid is to identify and characterize its various vulnerabilities. For complex networked systems such as cyber-enabled power systems this requires the development of modeling approaches that mimic salient interactions within the system. Interactions within a power system can be seperated into those related to the data acquisition, communication, processing and control (cyber components) and those related to the traditional power system (physical components). A smart grid would then have similar vulnerabilities to traditional communication and computer systems as well as those associated with the conventional power grid. Our research tries to identify cyber-physical vulnerabilities emerging from the somewhat emergent properties of cyber-physical interactions.
Our approaches to modeling make use of graphs and dynamical system tool-sets. A graph is a mathematical structure that represents pairwise relationships between a set of objects. A graph is defined by a collection of vertices (also called nodes) and a collection of edges that connect node pairs. Depending the use of a graph, its edges may or may not have direction leading to directed or undirected classes of graphs, respectively. Graphs provide a convenient and compact way to show cyber-physical relationships and relate dependencies within a power system. However, purely graph-based approaches do not sufficiently model the state changes within the physical system. Moreover, they do not effectively account for the unique characteristics of the system at various time-scales nor provide a convenient framework for modeling system physics. We assert that modeling the electrical grid is a vital component to an effective impact analysis framework.
One approach to physically modeling complex engineering interactions employs dynamical systems. A dynamical system is a mathematical formalization used to describe time-evolution of a state, which can typically represent a vector of physical quantities. The deterministic evolution rule describes the trajectory to future states from current states. Dynamical systems theory is motivated, in part, by ordinary differential equations and is well-suited to representing the complex physical interactions of the power grid.
We assert that a graph-based dynamical systems formulation is effective for a smart grid vulnerability assessment for a variety of reasons. First, effective smart grid attack analysis necessitates relating the cyber attack to physical consequences in the electricity network. A dynamical systems paradigm provides a flexible framework to model (with varying granularity and severity) the cause-effect relationships between the cyber data and the electrical grid state signals and ultimately relate them to power delivery metrics. Second, graphs enable a tighter coupling between the cyber and physical domains. For a smart grid, the cyber-to-physical connection is often represented through control signals that actuate change in the power system and the physical-to-cyber connection is typically due to the acquisition of power state sensor readings. These connections can be conveniently expressed as specifically located edges of the graphs. This way cascading failures and emergent properties from the highly coupled system can be represented. Mitigation approaches such as active control or islanding of the grid can naturally be portrayed to identify security mechanisms.
Our work takes on different flavors with the context of dynamical systems and graphs, and we propose two main modeling and vulnerability assessment approaches. One makes use of variable-structure system theory in order to identify and assess a class of reconfiguration vulnerabilities. Another makes use of a biologically-inspired approach to representing power and information flow as a flocking problem. Both approaches shed light on the cyber-physical system aspects of the smart grid to identify effective approaches for security and system hardening.
Related Course Resources
ECE1518: Seminar in Identity, Privacy and Security
Cyber-Physical Security of the Smart Grid
Related Publications
Distributed Demand Curtailment Via Water-Filling Inproceedings Proc. IEEE SmartGridComm, Miami, FL, 2015. |
Tuning Out of Phase: Resonance Attacks Inproceedings Proc. IEEE SmartGridComm, Miami, FL, 2015. |
A Systematic Approach to Delay-Adaptive Control Design for Smart Grids Inproceedings Proc. IEEE SmartGridComm, Miami, FL, 2015. |
On Using Distributed Energy Resources to Reshape the Dynamics of Power Systems During Transients Inproceedings Proc. IEEE SmartGridComm, Miami, FL, 2015. |
Secure Operating Regions Simplification in Dynamic Security Assessment Inproceedings Proc. IEEE SmartGridComm, Miami, FL, 2015. |
An Evolutionary Game Approach to Predict Demand Response From Real-Time Pricing Inproceedings Proc. IEEE Electrical Power and Energy Conference, London, ON, 2015. |
Network-Aware QoS Routing for Smart Grids Using Software Defined Networks Inproceedings Proc. EAI International Conference on Smart Grids for Smart Cities, 2015. |
Trends in Short-Term Renewable and Load Forecasting for Applications in Smart Grid Inproceedings Proc. EAI International Conference on Smart Grids for Smart Cities, 2015. |
Secure Management and Processing of Metered Data in the Cloud Inproceedings Proc. EAI International Conference on Smart Grids for Smart Cities, 2015. |
A Secure Cloud Architecture for Data Generated in the Energy Sector Inproceedings Proc. EAI International Conference on Smart Grids for Smart Cities, 2015. |
Distributed Optimization of Dispatch in Sustainable Generation Systems via Dual Decomposition Journal Article IEEE Transactions on Smart Grid, 6 (5), pp. 2501-2509, 2015. |
Robustness Analysis of Feedback Linearization Distributed Control Schemes in Smart Grid Systems Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. to appear, Denver, CO, 2015. |
Frequency-Stabilizing Control Scheme for Islanded Microgrids Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. to appear, Denver, CO, 2015. |
Paradigms and Performance of Distributed Cyber-Enabled Control Schemes for Smart Grid Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. to appear, Denver, CO, 2015. |
A Novel Evolutionary Game Theoretic Approach to Real-Time Distributed Demand Response Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. to appear, Denver, CO, 2015. |
Implementing Attacks for Modbus/TCP Protocol in a Real-Time Cyber Physical System Test Bed Inproceedings Proc. IEEE International Workshop Technical Committee on Communications Quality and Reliability, pp. 1-6, Charleston SC, 2015. |
On Using Distributed Control Schemes to Mitigate Switching Attacks in Smart Grids Inproceedings Proc. IEEE Canadian Conference on Electrical & Computer Engineering, pp. 1-5, Halifax NS, 2015. |
Cooperative Microgrid Networks for Remote and Rural Areas Inproceedings Proc. IEEE Canadian Conference on Electrical & Computer Engineering, pp. 1-6, Halifax NS, 2015. |
On the Effects of Distributed Control Area Design for the Stabilization of Cyber-Enabled Smart Grids Incollection Proc. IEEE Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, CPS Week, pp. 1-5, 2015. |
A Resilient Feedback Linearization Control Scheme for Smart Grids under Cyber-Physical Disturbances Inproceedings Proc. IEEE PES Innovative Smart Grid Technologies Conference, pp. 1-5, Washington DC, 2015. |
On Using Energy Storage Systems in Switching Attacks That Destabilize Smart Grid Systems Inproceedings Proc. IEEE PES Innovative Smart Grid Technologies Conference, pp. 1-5, Washington DC, 2015. |
A Cyber-Enabled Stabilizing Controller for Resilient Smart Grid Systems Inproceedings Proc. IEEE PES Innovative Smart Grid Technologies Conference, pp. 1-5, Washington DC, 2015. |
Grid-Independent Cooperative Microgrid Networks with High Renewable Penetration Inproceedings Proc. IEEE PES Innovative Smart Grid Technologies Conference, pp. 1-5, Washington DC, 2015. |
Distributed Sustainable Generation Dispatch via Evolutionary Games Inproceedings Proc. IEEE PES Innovative Smart Grid Technologies Conference, pp. 1-5, Washington DC, 2015. |
Denial of Service Attacks and Mitigation for Stability in Cyber-Enabled Power Grid Inproceedings Proc. IEEE PES Innovative Smart Grid Technologies Conference, pp. 1-5, Washington DC, 2015. |
On the use of Matroid Theory for Distributed Cyber-Physical-Constrained Generator Scheduling in Smart Grid Journal Article IEEE Transactions on Industrial Electronics, pp. 299-309, 2015. |
A Novel Bio-Inspired Technique for Rapid Real-Time Generator Coherency Identification Journal Article IEEE Transactions on Smart Grid, 6 (1), pp. 178-188, 2015. |
Cyber Attack Detection in PMU Measurements via the Expectation-Maximization Algorithm Inproceedings Proc. IEEE GlobalSIP Symposium on Energy Exchange and Intelligent Trading, Atlanta, GA, 2014. |
Performance of Flocking-Based Control Schemes in Smart Grid Applications Inproceedings Proc. IEEE GlobalSIP Symposium on Energy Exchange and Intelligent Trading, Atlanta, GA, 2014. |
Distributed Power Dispatch via Bifurcation Control Inproceedings Proc. IEEE GlobalSIP Symposium on Energy Exchange and Intelligent Trading, Atlanta, GA, 2014. |
A Flocking-Based Paradigm for Hierarchical Cyber-Physical Smart Grid Modeling and Control Journal Article IEEE Transactions on Smart Grid, 5 (6), pp. 2687-2700, 2014. |
A Game-Theoretic Control Approach to Mitigate Cyber Switching Attacks in Smart Grid Systems Inproceedings Proc. IEEE SmartGridComm, Venice, Italy, 2014. |
Performance Evaulation of Flocking-Based Distributed Cyber-Physical Control for Smart Grid Inproceedings Proc. IEEE SmartGridComm, Venice, Italy, 2014. |
Implementing a Real-Time Cyber-Physical System Test Bed in RTDS and OPNET Inproceedings Proc. IEEE North American Power Symposium, Pullman, Washington, 2014. |
Network Delay Caused by Cyber Attacks on SVC and its Impact on Transient Stability of Smart Grids Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. 1-5, Washington, DC, 2014. |
Practical Limitations of Sliding-Mode Switching Attacks on Smart Grid Systems Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. 1-5, Washington, DC, 2014. |
A Biologically Inspired Hierarchical Cyber-Physical Integrated Security Analysis Framework for Smart Grids PhD Thesis University of Toronto, 2014. |
A Coordinated Multi-Switch Attack for Cascading Failures in Smart Grid Journal Article IEEE Transactions on Smart Grid, 5 (4), pp. 1183-1195, 2014. |
Partition Based Cascaded Generator Scheduling with Constraints for Large Power Networks Inproceedings Proc. IEEE Global Conference on Signal and Information Processing, pp. 539-542, Austin, TX, 2013. |
A Framework for Modeling Cyber-Physical Switching Attacks in Smart Grid Journal Article IEEE Transactions on Emerging Topics in Computation Special Issue in Cyber-Physical Systems, 1 (2), pp. 273-285, 2013. |
Impact Analysis of Transient Stability Due to Cyber Attack on FACTS Devices Inproceedings Proc. North American Power Symposium, pp. 1-6, Kansas State University, 2013. |
Impact of Cyber Attacks on Transient Stability of Smart Grids with Voltage Support Devices Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. 1-5, Vancouver, Canada, 2013. |
Progressive Switching Attacks for Instigating Cascading Failures in Smart Grid Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. 1-5, Vancouver, Canada, 2013. |
A Multi-Flock Approach to Rapid Dynamic Generator Coherency Identification Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. 1-5, Vancouver, Canada, 2013. |
Coordinated Variable Structure Switching Attacks for Smart Grid PhD Thesis Texas A&M University, 2013. |
A Flocking-Based Model for DoS-Resilient Communication Routing in Smart Grid Inproceedings Proc. IEEE Global Communications Conference (GLOBECOM), Anaheim, CA, 2012. |
Probing the Telltale Physics: Towards a Cyber-Physical Protocol to Mitigate Information Corruption in Smart Grid Systems Inproceedings Proc. IEEE International Conferenceon Smart Grid Communications (SmartGridComm), Tainan City, Taiwan, 2012. |
Coordinated Variable Structure Switching Attack in the Presence of Model Error and State Estimation Inproceedings Proc. IEEE International Conferenceon Smart Grid Communications (SmartGridComm), Tainan City, Taiwan, 2012. |
A Flocking-Based Dynamical Systems Paradigm for Smart Power System Analysis Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. 1-8, San Diego, California, 2012. |
Two-Tier Hierarchical Cyber-Physical Security Analysis Framework For Smart Grid Inproceedings Proc. IEEE Power & Energy Society General Meeting, pp. 1-5, San Diego, California, 2012. |