JST-NSF-DFG-RCN Workshop on Data-driven Real-time Control for Distributed Energy Management, Tokyo, Japan, June 11-14, 2017

JST-NSF-DFG-RCN 分布式能源管理数据驱动实时控制研讨会，日本东京，2017 年 6 月 11-14 日

• 批准号: 1739146
• 负责人: Sairaj Dhople
• 金额: $ 4.5万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1739146&HistoricalAwards=false
• 关键词: JST; NSF; DFG; RCN; Workshop

The bulk power network is widely regarded as one of the most complex engineered systems. With the growing integration of distributed energy resources and the modernization of computing and communication systems, the complexity of interactions between constituent cyber and physical layers of the power system has vastly increased. Nevertheless, it is widely accepted that the systematic utilization of large data sets to inform distributed decision making can improve operational efficiency, power quality, and availability. Along these lines, this workshop will outline the foundational science for data-driven real-time control of distributed energy management systems.The workshop will bring together stakeholders with domain expertise in power systems and broader interests in related areas of data science, nonlinear systems, optimization, control theory, and circuit theory to address data-driven real-time control for next-generation power networks. Synthesis of distributed and decentralized control and optimization tasks while acknowledging large data streams is indeed a challenging task, and calls for complementary expertise in broad system-theoretic areas. Engagement with participants from Japan, Germany, and Norway will be critical, and it is anticipated that the workshop will highlight cutting-edge NSF-funded research on a truly international scale, and connect researchers from Germany, Japan, and Norway to those in the US towards realizing sustainable collaborative initiatives.

大容量电力网络被广泛认为是最复杂的工程系统之一。随着分布式能源资源的日益整合以及计算和通信系统的现代化，电力系统的网络层和物理层之间交互的复杂性大大增加。尽管如此，人们普遍认为，系统地利用大数据集来为分布式决策提供信息可以提高运营效率、电能质量和可用性。沿着这些思路，本次研讨会将概述分布式能源管理系统的数据驱动实时控制的基础科学。研讨会将汇集具有电力系统领域专业知识以及对数据科学、非线性系统、优化、控制理论和电路理论，以解决下一代电力网络的数据驱动实时控制问题。在承认大数据流的同时综合分布式和分散式控制和优化任务确实是一项具有挑战性的任务，需要广泛的系统理论领域的互补专业知识。来自日本、德国和挪威的参与者的参与至关重要，预计研讨会将重点介绍真正国际范围内由 NSF 资助的尖端研究，并将来自德国、日本和挪威的研究人员与其他国家的研究人员联系起来。美国致力于实现可持续的合作倡议。