BD Spokes: SPOKE: SOUTH: Collaborative: Smart Grids Big Data

BD Spokes：SPOKE：SOUTH：协作：智能电网大数据

• 批准号: 1636770
• 负责人: Zoran Obradovic
• 金额: $ 10万
• 依托单位: Temple University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1636770&HistoricalAwards=false
• 关键词: BD; Spokes; SPOKE; SOUTH; Collaborative

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.

美国电网现代化的一个固有特征是快速出现的大数据（BD）的存在。2009年的《美国复苏和再投资法案》（ARRA）拨款超过40亿美元，用于部署电网监测、控制和基础设施保护的新技术。 这导致大数据在多个运营领域的使用急剧增加，如发电，输电和配电，客户，服务和市场。一个具有挑战性的目标是将智能电网中的大数据转换为新的知识，这些知识非常丰富，但却没有得到充分利用，这些知识可以在上述智能电网运营领域提供重大改进，包括每年管理近万亿美元的电网基础设施，以及到2020年将建筑物的能源效率提高至少20%。智能电网BD（SGBD）Spoke将建立一个面向行动的组织，专注于为电力系统应用开发BD集成和知识提取的基本框架。这将使南方大数据中心能够应对社会的巨大挑战，即创建技术解决方案，以实现电力公用事业行业大数据分析所固有的经济潜力，预计到2020年将达到近40亿美元的年价值。该项目的使命是补充、加强和服务于南部枢纽的区域优先领域。此外，辐条的服务将有利于并补充其他枢纽区域优先领域，这些领域依赖于智能电网骨干的运营保证和弹性，特别是石油和天然气生产和分配，国家灾害（沿海和其他灾害），材料和制造，人居规划（智能和互联社区，交通，城市基础设施和可持续性）以及教育和培训。 智能电网大数据的重要性在于其来源、增长率和时空特征的多样性。开发大数据集成和知识提取的基本框架是一个巨大的挑战，因为科学和技术尚未被发现，理论框架尚未建立。其主要目标是创建一个组织，汇集来自学术界，工业界和政府的跨学科能力，从而（a）汇集来自不同大数据领域的人才和资源，以创建开放访问的大数据基础设施，实现协作和创新;（B）让行业参与定义其挑战，并实施新的大数据技术，以实现具有成本效益的计算、分析、和数据管理解决方案，以获得智能电网的全部好处;以及（c）与南方枢纽建立密切合作，以找到最有效的方式来发展推广，教育和培训，从而确保SGBD SPOKE域与其他枢纽域协同整合，以推进基础数据科学及其影响。 实现从智能电网大数据中提取知识将导致与大数据分析相关的多个学科领域的基础科学的进步。它还将增加我们对从物理系统收集的合并数据的理解，从而帮助我们更好地了解智能电网中的能量流动，以及这种理解如何预防紧急情况，改善资产管理和提高能源效率。它还将提供对行为分析的更透彻的理解，以解决与智能电力系统的人机界面。预期的转型成果是：（a）减少电网中断，提高能源和市场效率，减少碳排放，并使行业和客户参与新的商业模式，以确保行业增长，运营弹性和客户价值的解决方案，（B）一个跨领域的研究社区，专注于解决实际问题，同时推进对大数据问题的基本理解;以及（c）采用新颖的教学模式，在国内和全球教育和培训下一代大数据专家。