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Discipline: Computer Sciences & Information Management
Subcategory: STEM Research
Enrico Pontelli - New Mexico State University
Co-Author(s): Satish Ranade, New Mexico State University
The research effort performed as part of the iCREDITS mission – which is to develop the theoretical and practical foundations for the establishment of the smart grid paradigm. The proposed research takes a radical novel approach – it takes the perspective of the smart grid as a system of systems, composed of micro-grids that can be customer-driven. The design is essential to promote reliability and resilience, where each micro-grid has the opportunity to isolate from the main grid (e.g., to protect from cascading failures) and to operate as a unit (e.g., in negotiating prices and energy allocations). The research foundations are exploring three orthogonal aspects of such a system: 1. mathematical modeling of energy production, delivery, and consumption, in order to enable the understanding of how different components of a grid operate and interact. 2. development of novel communication protocols and infrastructures that enable the secure and reliable communication of the different types of information required within the grid. 3. development of algorithms to support coordination and decision making within the grid. The three research strands are inter-dependent and they eventually will result in actual devices and algorithms deployed in concrete micro-grids. The proposed design is aimed at ensuring two key properties of the grid: sustainability and resilience. Sustainability is viewed in two forms: design of infrastructures that will promote sustainability (e.g., environmental, economical) in energy management, and design of infrastructure that is, itself, sustainable (e.g., in terms of technology, economy, and policies). Resilience reflects the ability of the infrastructure to prevent, react, and adapt to unsual circumstances; resilience encompasses both protection from natural events as well as security from malicious attempts to disrupt operations. The smart grid and its components are expected to require a level of data collection and data exchange that are well beyond what we currently see on the internet (and from here the need, for example, for new communication infrastructures). As a result, the algorithms and models should accommodate for big data perspectives, leading to algorithms that are scalable and capable of using large and heterogenous data sets to guide decision making. Our research has launched exploration of how to discover patterns from energy transmission data indicating the potential of upcoming failures.
Funder Acknowledgement(s): HRD-1345232
Faculty Advisor: None Listed,
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