CRISP Type 2/Collaborative Research: Understanding the Benefits and Mitigating the Risks of Interdependence in Critical Infrastructure Systems

CRISP 类型 2/协作研究：了解关键基础设施系统相互依赖的好处并减轻风险

基本信息

批准号：
1735463
负责人：
Eytan Modiano
金额：
$ 119.99万
依托单位：
Massachusetts 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：
2018-01-01 至 2022-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1735463&HistoricalAwards=false
关键词：
CRISP Type Collaborative Research Understanding

项目摘要

This Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) project will identify new strategies to increase resilience in interdependent electric power, communication and natural gas networks. These three critical systems increasingly depend on one another to keep our energy and communication systems running. In some ways connections between these systems can make them work better, but in other ways connections can increase the chance of disastrous failures that could leave millions of people without heat, electricity or the ability to communicate. For example, a severe winter storm in the Northeastern United States could lead to both power grid failures and natural gas failures, leading to failures in telephone and Internet services, making it even more difficult to restore these critical services. Such "cascading failures" make it even harder for these systems to recover from natural disasters and intentional attacks. This project will identify strategies to make interdependent infrastructure systems more resilient to these cascading failures. Four Research Directions will combine to address this problem. Research Direction 1 will adapt new computational algorithms, such as Influence Graphs that can identify non-obvious critical connections and the Random Chemistry algorithm that can rapidly find critical triggering events, to the particular problems of cascading failures in interdependent infrastructure systems. Research Direction 2 will create new models of interdependence among natural gas, electric power and communication networks, which will form a testbed for computational algorithms. The resulting models will balance computational complexity and engineering detail by using detailed dynamical models of each system when necessary and simplified mathematical models when abstractions can be validated from real data. Research Direction 3 will develop and evaluate engineering solutions and coordination strategies that can mitigate harmful interdependencies and leverage beneficial interconnections. These will leverage insights from the application of new computational algorithms to the interdependence testbed, such as the identification of critical failure paths, to develop both real-time dynamic rescheduling algorithms and cost-effective long-term planning strategies. Research Direction 4 will use stakeholder interviews to evaluate the diverse ways that the electricity, natural gas, and communications industries understand risk, and facilitate discussion among key industry participants regarding interdependencies among these systems. The results will reveal the most effective paths to integrating new control and planning strategies to increase resilience in these diverse systems.This project will create significant societal benefits by uncovering new ways to reduce the risk of catastrophic failures among critical infrastructure systems. Because of interdependence among infrastructures, low probability, high cost cascading failures, which can have billions of dollars of economic and societal impacts, can contribute more to overall risk, relative to more frequent, small events. Reducing this risk can have enormous benefits to society. To ensure that results from this project have practical impacts the team will be guided by a Research Advisory Board that includes a large power grid operator (ISO New England), a software vendor for the electricity industry (GE/Alstom), a natural gas company (Vermont Gas), and the MITRE corporation. Furthermore, the project will integrate education and research through new curriculum and outreach to high school students. Public data that result from this project will be released through the github repository at: https://github.com/phines/infrastructure-risk, as well as through the project web site at http://www.uvm.edu/~tesla/project/nsf-crisp/. All research data associated with this project, including public and non-public data, will be preserved for at least 5 years after the end of the project.

这个关键的韧性相互依存的基础设施系统和流程（CRISP）项目将确定新的策略，以提高相互依存的电力，通信和天然气网络的弹性。这三个关键系统越来越依赖彼此，以保持我们的能量和通信系统运行。在某些方面，这些系统之间的连接可以使它们变得更好，但是在其他方面，连接可能会增加灾难性失败的机会，这可能会使数百万的人没有热，电或交流能力。例如，美国东北部的冬季风暴可能导致电网故障和天然气故障，导致电话和互联网服务失败，从而使恢复这些关键服务更加困难。这种“级联故障”使这些系统更难从自然灾害和故意攻击中恢复。该项目将确定使相互依存的基础架构系统对这些级联故障更具弹性的策略。四个研究方向将结合解决这个问题。研究方向1将适应新的计算算法，例如可以识别非明显关键连接的影响图和可以迅速找到关键触发事件的随机化学算法，以及相互依存基础结构系统中级联故障的特定问题。研究方向2将在天然气，电力和通信网络中创建新的相互依赖模型，该模型将形成计算算法的测试台。最终的模型将在必要时使用每个系统的详细动力学模型来平衡计算复杂性和工程细节，并且在可以从真实数据验证抽象时进行了简化的数学模型。研究方向3将制定和评估工程解决方案和协调策略，这些策略可以减轻有害的相互依赖性并利用有益的互连。这些将利用从新计算算法到相互依赖测试台的应用，例如识别关键故障路径的洞察力，以开发实时动态重新安排算法和成本效益的长期计划策略。研究方向4将使用利益相关者访谈来评估电力，天然气和通信行业理解风险的多种方式，并促进关键行业参与者在这些系统之间就相互依赖性的讨论。结果将揭示整合新的控制和计划策略以提高这些多样化系统中的弹性的最有效途径。本项目将通过发现新的方法来减少关键基础设施系统中灾难性失败的风险来创造重大的社会收益。由于基础设施之间的相互依存关系，低概率，高成本的级联失败可能会产生数十亿美元的经济和社会影响，因此相对于更频繁的小事件，可以对整体风险产生更大的贡献。降低这种风险可能会对社会带来巨大的利益。为了确保该项目的结果具有实际影响，团队将由一个研究咨询委员会指导，其中包括大型电网运营商（ISO New England），电力行业的软件供应商（GE/ALSTOM），天然气公司（Vermont Gas）（Vermont Gas）和Miter Corporation。此外，该项目将通过新的课程和向高中生的宣传来整合教育和研究。 Public data that result from this project will be released through the github repository at: https://github.com/phines/infrastructure-risk, as well as through the project web site at http://www.uvm.edu/~tesla/project/nsf-crisp/.与该项目相关的所有研究数据，包括公共和非公共数据，将在项目结束结束后至少保存5年。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Data-driven Localization and Estimation of Disturbance in the Interconnected Power System

DOI：
10.1109/smartgridcomm.2018.8587509
发表时间：
2018-06
期刊：
2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
影响因子：
0
作者：
Hyang-Won Lee;Jianan Zhang;E. Modiano
通讯作者：
Hyang-Won Lee;Jianan Zhang;E. Modiano

Regional foundations of energy transitions