The national transmission networks that deliver high voltage electric power underpin our society and are central to the ongoing transformation of the American energy infrastructure. Transmission networks are very large and complicated engineering systems, and "keeping the lights on" as the transformation of the American energy infrastructure proceeds is a fundamental engineering challenge involving both the physical aspects of the equipment and the cyber aspects of the controls, communications, and computers that run the system. The project develops new principles of cyber-physical engineering by focusing on instabilities of electric power networks that can cause blackouts. It proposes novel approaches to analyze these instabilities and to design cyber-physical control methods to monitor, detect, and mitigate them. The controls must perform robustly in the presence of variability and uncertainty in electric generation, loads, communications, and equipment status, and during abnormal states caused by natural faults or malicious attacks. The research produces cyber-physical engineering methodologies that specifically help to mitigate power system blackouts and more generally show the way forward in designing robust cyber-physical systems in environments characterized by rich dynamics and uncertainty. Education and outreach efforts involve students at high school, undergraduate, and graduate levels, as well as dissemination of results to the public and the engineering and applied science communities in industry, government and universities.

The objective of this research is to understand how pervasive information changes energy production, distribution and use. The design of a more scalable and flexible electric infrastructure, encouraging efficient use, integrating local generation, and managing demand through awareness of energy availability and use over time, is investigated. The approach is to develop a cyber overlay on the energy distribution system in its physical manifestations: machine rooms, buildings, neighborhoods, isolated generation islands and regional grids. A scaled series of experimental energy networks will be constructed, to demonstrate monitoring, negotiation protocols, control algorithms and Intelligent Power Switches integrating information and energy flows in a datacenter, building, renewable energy: farm", and off-grid village. These will be generalized and validated through larger scale simulations. The proposal's intellectual merit is in understanding broadly how information enables energy efficiencies: through intelligent matching of loads to sources, via various levels of aggregation, and by managing how and when energy is delivered to demand, adapted in time and form to available supply. Bi-directional information exchange is integrated everywhere that power is transferred. Broader impacts include training diverse students, such as undergraduates and underrepresented groups, in a new interdisciplinary curriculum in information and energy technologies. Societal impact is achieved by demonstrating dramatic reductions in the carbon footprint of energy and its overall usage, greater penetration of renewables while avoiding additional fossil fuel plants, and shaping a new culture of energy awareness and management. The evolution of Computer Science will be accelerated to meet the challenges of cyber-physical information processing.

The objective of this research is the development of methods for the control of energy flow in buildings, as enabled by cyber infrastructure. The approach is inherently interdisciplinary, bringing together electrical and mechanical engineers alongside computer scientists to advance the state of the art in simulation, design, specification and control of buildings with multiple forms of energy systems, including generation and storage. A significant novelty of this project lies in a fundamental view of a building as a set of overlapping, interacting networks. These networks include the thermal network of the physical building, the energy distribution network, the sensing and control network, as well as the human network, which in the past have been considered only separately. This work thus seeks to develop methods for simulating, optimizing, modeling, and control of complex, heterogeneous networks, with specific application to energy efficient buildings. The advent of maturing distributed and renewable energy sources for on-site cooling, heating, and power production and the concomitant developments in the areas of cyberphysical and microgrid systems present an enormous opportunity to substantially increase energy efficiency and reduce energy-related emissions in the commercial building energy sector. In addition, there is a direct impact of the proposed work in training students with backgrounds in the unique blend of engineering and computer science that is needed for the study of cyber-enabled energy efficient management of structures, as well as planned interactions at the undergraduate and K-12 level.

The objective of this research is to develop methods to monitor and ensure the robustness of a class of cyber-physical systems termed "physical networks," such as electric, water, sewage, and gas networks. The approach is to analyze such networks using the mathematical formalism of graphical models. The project models a physical network as a graph, whose variables have a concrete physical interpretation, such as voltage, satisfying known physical laws, such as Kirchoff laws. The machinery of graphical models is used to develop methods to monitor and ensure the robustness of such networks, using the electric power network as a representative. By studying puzzling network-wide interactions, the project has the potential to clarify the role of complexity in large scale networks. Potential contributions will be made to the fields of distributed inference algorithms and fast numerical methods. Physical networks play a crucial role in modern society, and yet, often exhibit fragile behavior, such as black-outs in electric power networks, resulting in economic loss, as well as causing a security risk. This project seeks to understand the robustness behavior of such networks and to train a broad class of students in their theory and practice. Results from this research are to be incorporated into courses and disseminated via research publications. The Carnegie Mellon Conference on the Electricity Industry allows students to interact with faculty and electricity industry veterans. Interaction with the electricity industry aims to provide it with an understanding of cyber-intelligence, to ensure effective robustness monitoring capabilities in the power grid.