CPS: Synergy: Collaborative Research: Distributed Asynchronous Algorithms and Software Systems for Wide-Area Monitoring of Power Systems

CPS：协同：协作研究：用于电力系统广域监控的分布式异步算法和软件系统

• 批准号: 1329780
• 负责人: Aranya Chakrabortty
• 金额: $ 40万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1329780&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Distributed

The objective of this proposal is to develop a distributed algorithmic framework, supported by a highly fault-tolerant software system, for executing critical transmission-level operations of the North American power grid using gigantic volumes of Synchrophasor data. As the number of Phasor Measurement Units (PMU) increases to more than thousands in the next 4-5 years, it is rather intuitive that the current state-of-the-art centralized communication and information processing architecture of Wide-Area Measurement System (WAMS) will no longer be sustainable under such data-explosion, and a completely distributed cyber-physical architecture will need to be developed. The North American Synchrophasor Initiative (NASPI) is currently addressing this architectural aspect by developing new communication and computing protocols through NASPI-net and Phasor Gateway. However, very little attention has been paid so far to perhaps the most critical consequence of this envisioned distributed architecture "namely", distributed algorithms, and their relevant middleware. Our primary task, therefore, will be to develop parallel computational methods for solving real-time wide-area monitoring and control problems with analytical investigation of their stability, convergence and robustness properties, followed by their implementation and testing against extraneous malicious attacks using our WAMS-RTDS testbed at NC State. In particular, we will address three critical research problems "namely" distributed wide-area oscillation monitoring, transient stability assessment, and voltage stability monitoring.The intellectual merit of this research will be in establishing an extremely timely application area of the PMU technology through its integration with distributed computing and optimal control. It will illustrate how ideas from advanced ideas from numerical methods and distributed optimization can be combined into power system monitoring and control applications, and how they can be implemented via fault-tolerant computing to maintain grid stability in face of catastrophic cyber and physical disturbances.The broader impact of this project will be in providing a much-needed application of CPS engineering to advance emerging research on PMU-integrated next-generation smart grids. Research results will be broadcast through journal publications, jointly organized graduate courses between NC State and University of Illinois Urbana Champagne, conference tutorials and workshops. Undergraduate research for minority engineering students will be promoted via the FREEDM Systems Center, summer internships via Information Trust Institute (UIUC) and RENCI, and middle/high-school student mentoring through the NCSU Science House program.

该提案的目的是开发一个由高度容忍故障的软件系统支持的分布式算法框架，用于使用巨大的同步声数据来执行北美电力网格的关键传输级操作。在未来4 - 5年内，相量测量单元（PMU）的数量增加到了数千个以上，因此，在此类数据探索的情况下，广阔区域测量系统（WAMS）的当前最先进的集中式沟通和信息处理架构将不再可持续，并且在此类数据探索下不再是可持续的，并且需要完全分散的网络构建构造，并且需要开发出来。北美同步倡议（NASPI）目前正在通过通过NASPI-NET和Phasor Gateway开发新的通信和计算协议来解决这一建筑方面。但是，到目前为止，很少有人关注这种设想的分布式体系结构，即分布式算法及其相关中间件的最关键后果。因此，我们的主要任务将是开发平行的计算方法，以通过对其稳定性，收敛性和鲁棒性特性进行分析调查，以解决实时广泛的区域监测和控制问题，然后使用我们的WAMS-RTDS测试在NC州进行实施和测试，以针对无关的恶意攻击进行测试。特别是，我们将“分布”分布的大区域振荡监测，瞬态稳定性评估和电压稳定性监测“分布”的三个关键研究问题。这项研究的智力优点将是通过与分布式计算和最佳控制的集成来建立PMU技术的极其及时的应用领域。 It will illustrate how ideas from advanced ideas from numerical methods and distributed optimization can be combined into power system monitoring and control applications, and how they can be implemented via fault-tolerant computing to maintain grid stability in face of catastrophic cyber and physical disturbances.The broader impact of this project will be in providing a much-needed application of CPS engineering to advance emerging research on PMU-integrated next-generation smart grids.研究结果将通过期刊出版物，北卡罗来纳州州立大学和伊利诺伊大学乌尔巴纳大学香槟，会议教程和研讨会之间的共同组织的研究生课程播出。将通过Freedm Systems Center，Information Trust Institute（UIUC）和Renci的暑期实习以及通过NCSU Science House计划的中级/高中生指导来促进少数民族工程专业学生的本科研究。

项目成果

Work-in-Progress: Making Machine Learning Real-Time Predictable

• DOI: 10.1109/rtss.2018.00029
• 发表时间: 2018-12
• 期刊: 2018 IEEE Real-Time Systems Symposium (RTSS)
• 作者: Hang Xu;F. Mueller