This project develops an integrated framework of communications, computation and control for understanding wide-area power system performance in the face of unpredictable disturbances. The power system is chosen as a particularly challenging cyber physical system (CPS) due to its extreme dimension, geographic reach and high reliability requirements. The following tasks are studied in the proposed research: (a) a Partial Difference Equation (PdE) framework to model the impact of network topology on the power system stability; (b) the design of a communication network for CPS, based on the PdE modeling;(c) the design of a control system, which addresses the challenges such as fast response and resource constraints; (d) the design of a computing infrastructure, which addresses the computation for controlling the power network, in particular, the communication complexity for controlling the power network in both cases of one-snapshot computation and iterative computations; and (e) the test and evaluation for both small scale system models of several hundred buses and very large system models of ~50,000 buses. This work contributes to the broader understanding of CPS with high reliability requirements, particularly, critical infrastructures such as the power grid. Modern infrastructures are complex systems of communications and computation tied to the controls of the physical system. The proposed research contributes to improved reliability by addressing the propagation of disturbances and advancing the understanding of geographically distributed CPS. The PIs plan to open multiple courses on CPS related to the proposed research.

Energy infrastructure is a critical underpinning of modern society. To ensure its reliable operation, a nation-wide or continent-wide situational awareness system is essential to provide high-resolution understanding of the system dynamics such that proper actions can be taken in real-time in response to power system disturbances and to avoid cascading blackouts. The power grid represents a typical highly dynamic cyber-physical system (CPS). The ever-increasing complexity and scale in sensing and actuation, compounded by the limited knowledge of the accurate system state have resulted in major system failures, such as the massive power blackout of August 2003 and the most recent Arizona/California blackout of September 2011. Therefore, methods and tools for monitoring and control of these and other such dynamic systems at high resolution are vital to an emergent generation of tightly coupled, physically distributed CPS. This project employs the power grid as a target application and develops a high-resolution, ultra-wide-area situational awareness system that synergistically integrates sensing, processing, and actuation. First, from the sensing perspective, high resolution is reflected in both measurement accuracy and potential for dense spatial coverage. Wide area, precise, synchronized, and affordable sensing in voltage angle and frequency measurements for large-scale observation is sorely needed to observe system disturbances and capture critical changes in the power grid. The crucial innovation of this work is to make accurate frequency measurement from low voltage distribution systems through the wide deployment of Frequency Disturbance Recorders (FDRs). Second, from a data processing perspective, high resolution is reflected in finer-scale data analysis to reveal hidden information. In practical CPS, events seldom occur in an isolated fashion; cascading events are more common and realistic. A new conceptual framework is presented in the study of event analysis, referred to as event unmixing, where real-world events are considered a mixture of more than one constituent root event. This concept is a key enabler for the analysis of events to go beyond what are immediately detectable in the system. The event formation process is interpreted from a linear mixing perspective and innovative sparsity-constrained unmixing algorithms are presented for multiple event separation and spatial-temporal localization. Third, to discover the high-level spatial-temporal correlation among root events in real time, a descriptive language is developed to discover patterns on the spatial and temporal information of root events. This descriptive language allows embedding pattern descriptions on the desirable and undesirable interactions between events in the system, which will then be compiled into distributed runtime constructs to be executed in deployed systems. Fourth, from the actuation perspective, the system pushes the intelligence toward the lower level of the power grid allowing local devices to make decisions and to react quickly to contingencies based on the high-resolution understanding of the system state, enabling a more direct reconfiguration of the physical makeup of the grid. Finally, the methods and tools are implemented and validated on an existing wide-area power grid monitoring system, the North American frequency monitoring network (FNET). Escalating demands for electricity coupled with an outdated power transmission grid pose a serious threat to the US economy. The transformative nature of this research is to turn a large volume of real-time data into actionable information and help prevent potential outages from happening. The power grid is a typical example of dynamic cyber physical system. Providing high-resolution situational awareness for the power grid has a direct and immediate impact on this and other CPS. The research is coupled with a strong educational component including active recruitment of students from underrepresented groups supported by existing programs and broad dissemination of research findings.

The project aims at making cities "smarter" by engineering processes such as traffic control, efficient parking services, and new urban activities such as recharging electric vehicles. To that end, the research will study the components needed to establish a Cyber-Physical Infrastructure for urban environments and address fundamental problems that involve data collection, resource allocation, real-time decision making, safety, and security. Accordingly, the research is organized along two main directions: (i) Sensing and data acquisition using a new mobile sensor network paradigm designed for urban environments; and (ii) Decision Support for the "Smart City" relying on formal verification and certification methods coupled with innovative dynamic optimization techniques used for decision making and resource allocation. The work will bring together and build upon methodological advances in optimization under uncertainty, computer simulation, discrete event and hybrid systems, control and games, system security, and formal verification and safety. Target applications include: a "Smart Parking" system where parking spaces are optimally assigned and reserved, and vehicular traffic regulation. The research has the potential of revolutionizing the way cities are viewed: from a passive living and working environment to a highly dynamic one with new ways to deal with transportation, energy, and safety. Teaming up with stakeholders in the Boston Back Bay neighborhood, the City of Boston, and private industry, the research team expects to establish new collaborative models between universities and urban groups for cutting-edge research embedded in the deployment of an exciting technological, economic, and sociological development.

Large-scale critical infrastructure systems, including energy and transportation networks, comprise millions of individual elements (human, software and hardware) whose actions may be inconsequential in isolation but profoundly important in aggregate. The focus of this project is on the coordination of these elements via ubiquitous sensing, communications, computation, and control, with an emphasis on the electric grid. The project integrates ideas from economics and behavioral science into frameworks grounded in control theory and power systems. Our central construct is that of a ?resource cluster,? a collection of distributed resources (ex: solar PV, storage, deferrable loads) that can be coordinated to efficiently and reliably offer services (ex: power delivery) in the face of uncertainty (ex: PV output, consumer behavior). Three topic areas form the core of the project: (a) the theoretical foundations for the ?cluster manager? concept and complementary tools to characterize the capabilities of a resource cluster; (b) centralized resource coordination strategies that span multiple time scales via innovations in stochastic optimal control theory; and (c) decentralized coordination strategies based on cluster manager incentives and built upon foundations of non-cooperative dynamic game theory. These innovations will improve the operation of infrastructure systems via a cyber-physical-social approach to the problem of resource allocation in complex infrastructures. By transforming the role of humans from passive resource recipients to active participants in the electric power system, the project will facilitate energy security for the nation, and climate change mitigation. The project will also engage K-12 students through lab-visits and lectures; address the undergraduate demand for power systems training through curricular innovations at the intersection of cyber-systems engineering and physical power systems; and equip graduate students with the multi-disciplinary training in power systems, communications, control, optimization and economics to become leaders in innovation.

The most compelling problem confronting detection of nuclear material in a large area is the level of manifest uncertainty. Furthermore, detection and localization problems involve nontrivial and nonlinear non-convex optimization often stuck at local minima. This project develops fundamentally new techniques by using cheap detectors for rough detection and localization, placing detectors to expunge local minima, achieving fast distributed localization with reduced communication overheads, simultaneously localizing multiple sources and optimally placing detectors and assisting in their autonomous self-organization. There is a growing recognition of the inadequacy of current capabilities with respect to nuclear material detection and localization in public events and areas. This project develops an integrated cyber-physical system for public protection against nuclear and radiological threats. Clearly the project addresses a national security issue. If successful, the contribution and results of the project likely open a new framework for detection or monitoring in a large area using a wireless detector network. One of the key aspects of this project is the inter-disciplinary training of our graduate and undergraduate students including female and minority students in the areas of signal processing, statistical methods, modeling and performance analysis. K-12 students are also targeted through the First competition and Project-Lead-The-Way that connects the College of Engineering at the University of Iowa to almost all high school students in Iowa. It is expected that the project will generate enthusiasm and interests in science, mathematics and engineering for high school students.