BD Spokes: SPOKE: South: Collaborative: Smart Grids Big Data
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An inherent feature of the modernization of America''s electrical power grid is a rapidly emerging Big Data (BD) presence. The American Recovery and Reinvestment Act (ARRA) of 2009 allocated over $4 billion to deployment of new technology for grid monitoring, control and infrastructure protection. This led to a dramatic proliferation in the use of Big Data across multiple operational domains such as generation, transmission and distribution, customers, services, and markets. A challenging goal is to convert Big Data in smart grids, which is overwhelmingly abundant and yet grossly underutilized, into new knowledge that can offer major improvements in the above mentioned domains of smart grid operation, including management of almost a trillion dollars in grid infrastructure annually and an increase in building energy efficiency by at least 20% by 2020. The Smart Grids BD (SGBD) Spoke will build an action-oriented organization focused on developing the fundamental framework for BD integration and knowledge extraction for power system applications. This will enable the South Big Data Hub to meet the societal grand challenge of creating technological solutions that can fulfill the economic potential inherent in Big Data analytics in the electric utility industry, expected to reach an annual value of close to $4 billion by 2020. The Project mission is to complement, strengthen, and serve the South Hub regional priority areas. Moreover, the services of the Spoke will benefit and complement the other Hub regional priority areas dependent on a smart grid backbone for operational assurance and resilience, specifically the areas of Oil and Gas Production and Distribution, National Hazards (Coastal and Other Hazards), Materials and Manufacturing, Habitat Planning (Smart and Connected Communities, Transportation, Urban Infrastructure and Sustainability) and Education and Training.The significance of Smart Grids Big Data is in the diversity of its sources, growth rate, and spatiotemporal characteristics. Developing a fundamental framework for Big Data integration and knowledge extraction is a grand challenge since the science and technology are yet to be discovered and the theoretical framework established. The main objective is to create an organization that brings together a cross disciplinary capability from academia, industry, and government, thereby (a) bringing talent and resources from diverse Big Data areas to create an open access Big Data infrastructure that enables collaboration and innovation; (b) engaging industry to define its challenges and implement new Big Data technologies for cost-effective computational, analytical, and data management solutions needed to get the full benefits of smart grids; and (c) establishing close collaboration with the South Hub to find the most effective way to develop outreach, education, and training, thereby assuring the SGBD SPOKE domain integrates synergistically with the other Hub domains to advance fundamental data science and its impacts. Achieving the knowledge extraction from Smart Grids Big Data will result in the advancement of fundamental sciences in multiple disciplinary domains related to Big Data analytics. It will also increase our understanding of merged data collected from the physical systems, thereby helping us better understand the flow of energy in the smart grids, and how this understanding can prevent emergencies, improve asset management, and increase energy efficiency. It will also provide a more illuminated understanding of behavioral analytics that addresses the human interface with smart electricity systems. The expected transformational outcomes are: (a) solutions to decreasing the grid outages, improving energy and market efficiency, reducing carbon emissions, and engaging industry and customers in new business models to ensure industry growth, operational resiliency, and customer value, (b) a cross cutting research community focused on solving practical problems while concurrently advancing the fundamental understanding of Big Data issues; and (c) engaging novel instructional paradigms for educating and training the next generation of Big Data experts nationally and globally.