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.

本提案的目标是开发一个分布式算法框架，由一个高度容错的软件系统支持，用于执行关键的传输级操作的北美电网使用巨大的同步相量数据。随着相量测量单元（PMU）的数量在未来4-5年内增加到数千个以上，相当直观的是，在这种数据爆炸下，当前最先进的广域测量系统（WAMS）的集中式通信和信息处理架构将不再可持续，并且需要开发完全分布式的信息物理架构。北美同步相量计划（NASPI）目前正在通过NASPI网络和相量网关开发新的通信和计算协议来解决这一体系结构方面的问题。然而，很少有人注意到，到目前为止，也许是最关键的后果，这种设想的分布式体系结构“即”，分布式算法，及其相关的中间件。因此，我们的主要任务将是开发并行计算方法，用于解决实时广域监测和控制问题，并对其稳定性，收敛性和鲁棒性进行分析研究，然后使用我们在NC State的WAMS-RTDS测试平台对外部恶意攻击进行实施和测试。特别是分布式广域振荡监测、暂态稳定性评估和电压稳定性监测这三个关键性的研究课题，其智力价值在于通过与分布式计算和最优控制的结合，为PMU技术建立一个非常及时的应用领域。它将说明如何将数值方法和分布式优化的先进思想结合到电力系统监测和控制应用中，以及如何通过容错计算来实现它们，以在灾难性的网络和物理干扰面前保持电网稳定。该项目的更广泛影响将是提供急需的CPS工程应用，以推进PMU的新兴研究。下一代智能电网。研究结果将通过期刊出版物，北卡罗来纳州和伊利诺伊大学厄巴纳香槟，会议教程和研讨会之间联合举办的研究生课程广播。少数民族工程专业学生的本科研究将通过FREEDM系统中心，通过信息信任研究所（UIUC）和RENCI的暑期实习，以及通过NCSU科学之家计划的初中/高中学生辅导来促进。

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