This project addresses the impact of the integration of renewable intermittent generation in a power grid. This includes the consideration of sophisticated sensing, communication, and actuation capabilities on the system's reliability, price volatility, and economic and environmental efficiency. Without careful crafting of its architecture, the future smart grid may suffer from a decrease in reliability. Volatility of prices may increase, and the source of high prices may be more difficult to identify because of undetectable strategic policies. This project addresses these challenges by relying on the following components: (a) the development of tractable cross-layer models; physical, cyber, and economic, that capture the fundamental tradeoffs between reliability, price volatility, and economic and environmental efficiency, (b) the development of computational tools for quantifying the value of information on decision making at various levels, (c) the development of tools for performing distributed robust control design at the distribution level in the presence of information constraints, (d) the development of dynamic economic models that can address the real-time impact of consumer's feedback on future electricity markets, and finally (e) the development of cross-layer design principles and metrics that address critical architectural issues of the future grid. This project promotes modernization of the grid by reducing the system-level barriers for integration of new technologies, including the integration of new renewable energy resources. Understanding fundamental limits of performance is indispensable to policymakers that are currently engaged in revamping the infrastructure of our energy system. It is critical that we ensure that the transition to a smarter electricity infrastructure does not jeopardize the reliability of our electricity supply twenty years down the road. The educational efforts and outreach activities will provide multidisciplinary training for students in engineering, economics, and mathematics, and will raise awareness about the exciting research challenges required to create a sustainable energy future.

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 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.

This project addresses the impact of the integration of renewable intermittent generation in a power grid. This includes the consideration of sophisticated sensing, communication, and actuation capabilities on the system's reliability, price volatility, and economic and environmental efficiency. Without careful crafting of its architecture, the future smart grid may suffer from a decrease in reliability. Volatility of prices may increase, and the source of high prices may be more difficult to identify because of undetectable strategic policies. This project addresses these challenges by relying on the following components: (a) the development of tractable cross-layer models; physical, cyber, and economic, that capture the fundamental tradeoffs between reliability, price volatility, and economic and environmental efficiency, (b) the development of computational tools for quantifying the value of information on decision making at various levels, (c) the development of tools for performing distributed robust control design at the distribution level in the presence of information constraints, (d) the development of dynamic economic models that can address the real-time impact of consumer's feedback on future electricity markets, and finally (e) the development of cross-layer design principles and metrics that address critical architectural issues of the future grid. This project promotes modernization of the grid by reducing the system-level barriers for integration of new technologies, including the integration of new renewable energy resources. Understanding fundamental limits of performance is indispensable to policymakers that are currently engaged in revamping the infrastructure of our energy system. It is critical that we ensure that the transition to a smarter electricity infrastructure does not jeopardize the reliability of our electricity supply twenty years down the road. The educational efforts and outreach activities will provide multidisciplinary training for students in engineering, economics, and mathematics, and will raise awareness about the exciting research challenges required to create a sustainable energy future.

The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions. This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances. The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.

The electric grid in the United States has evolved over the past century from a series of small independent community-based systems to one of the largest and most complex cyber-physical systems today. However, the established conditions that made the electric grid an engineering marvel are being challenged by major changes, the most important being a worldwide effort to mitigate climate change by reducing carbon emissions. This research investigates key aspects of a computation and information foundation for future cyber-physical energy systems?the smart grids. The overall project objective is to support high penetrations of renewable energy sources, community based micro-grids, and the widespread use of electric cars and smart appliances. The research has three interconnected components that, collectively, address issues of computation architecture, information hierarchy, and experimental modeling and validation. On computation architecture, the framework based on cloud computing is investigated for the scalable, consistent, and secure operations of smart grids. The research aims to quantify fundamental design tradeoffs among scalability, data consistency, security, and trustworthiness for emerging applications of smart grids. On information hierarchy, temporal and spatial characteristics of information hierarchy are investigated with the goal of gaining a foundational understanding on how information should be partitioned, collected, distributed, compressed, and aggregated. The research also develops an open and scalable experimental platform (SmartGridLab) for empirical investigations and testing of algorithms and concepts developed in this project. SmartGridLab integrates the hardware testbed with a software simulator so that software virtual nodes can interact with physical nodes in the testbed. This research also includes a significant education component aimed at integrating frontier research with undergraduate and graduate curricula.