CPS:Synergy:Collaborative Research: Real-time Data Analytics for Energy Cyber-Physical Systems

CPS：协同：协作研究：能源网络物理系统的实时数据分析

• 批准号: 1854077
• 负责人: Maggie Cheng
• 金额: $ 33.61万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1854077&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Real

Inadequate system understanding and inadequate situational awareness have caused large-scale power outages in the past. With the increased reliance on variable energy supply sources, system understanding and situational awareness of a complex energy system become more challenging. This project leverages the power of big data analytics to directly improve system understanding and situational awareness. The research provides the methodology for detecting anomalous events in real-time, and therefore allow control centers to take appropriate control actions before minor events develop into major blackouts. The significance for the society and for the power industry is profound. Energy providers will be able to prevent large-scale power outages and reduce revenue losses, and customers will benefit from reliable energy delivery with service guarantees. Students, including women and underrepresented groups, will be trained for the future workforce in this area.The project includes four major thrusts: 1) real-time anomaly detection from measurement data; 2) real-time event diagnosis and interpretation of changes in the state of the network; 3) real-time optimal control of the power grid; 4) scientific foundations underpinning cyber-physical systems. The major outcome of this project is practical solutions to event or fault detection and diagnosis in the power grid, as well as prediction and prevention of large-scale power outages.

过去，由于对系统认识不足和对形势认识不足，造成了大规模停电。随着对可变能源的日益依赖，对复杂能源系统的系统理解和情景认识变得更加具有挑战性。该项目利用大数据分析的力量，直接提高系统理解和态势感知能力。这项研究提供了实时检测异常事件的方法，从而使控制中心能够在小事件发展成大停电之前采取适当的控制行动。这对社会和电力行业都具有深远的意义。能源供应商将能够防止大规模停电并减少收入损失，客户将受益于具有服务保证的可靠能源输送。学生，包括妇女和代表不足的群体，将接受这一领域未来劳动力的培训。该项目包括四个主要方面：1)从测量数据中实时检测异常；2)实时事件诊断和网络状态变化的解释；3)电网的实时优化控制；4)支撑网络物理系统的科学基础。该项目的主要成果是为电网中的事件或故障检测和诊断以及大规模停电的预测和预防提供了实用的解决方案。