Modernized electrical grid automated to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity.
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GRID 2020: The power grid in the U.S. and many regions of the world is undergoing changes because of new technologies and government mandates. It is believed that smart meters and a smarter grid will lead to more efficient use of our infrastructure. In addition, increased renewable energy integration will provide power at low cost.
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Data-driven intelligence is an essential foundation for physical systems in transportation safety and efficiency, area surveillance and security, as well as environmental sustainability. While sophisticated data analysis and synthesis can be well supported in large data centers, future intelligent systems require on-the-scene processing with faster responses and less dependence on the unreliable (often wireless) data communications in the field.
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This project will design next-generation defense mechanisms to protect critical infrastructures, such as power grids, large industrial plants, and water distribution systems. These critical infrastructures are complex primarily due to the integration of cyber and physical components, the presence of high-order behaviors and functions, and an intricate and large interconnection pattern.
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Many practical systems can be categorized as cyber physical systems (CPSs), such as smart grid, unmanned aerial vehicles (UAVs) and robotic networks. A typical CPS consists of physical dynamics, sensors, communication network and controllers. The communication network is of key importance in CPS, since it mimics the nerve system in the human body. Hence, it is critical to study how the communication network in CPS should be analyzed and designed.
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In this project, we are working on the broad problem of maximizing the penetration of renewables in smart grid. To that end, we are developing strategies for optimal demand response, operation, and real-time pricing. In particular, we propose theory for optimal operation for the independent system operator (ISO), and for the load serving entity (LSE).
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Commodity operating systems manage time in a best effort fashion, where clock synchronization is performed independently of both application demand and resource constraints. The vision of the RoseLine project is to develop a Quality of Time (QoT) stack for Linux that enables developers to write distributed applications that perform computation with a common sense of time.
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Existing platforms are built with a static network connecting microprocessor, radio, clock system, and other components. This static configuration prevents researchers from experimentally validating the trade-offs between the way that clocks are conditioned and distributed, and the performance of the embedded system. In particular, such design decisions have major impact on time synchronization.
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This project is focused on developing a fundamental understanding of the impact of network delays and data drops using an approach that is applicable to a variety of Cyber-Physical Systems (CPS). An example of such a CPS is the power grid which includes large-scale deployment of distributed and networked Phasor Measurement Units (PMUs) and wind energy resources.
