• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

通过增加基础设施网络的相互依存关系来降低级联故障风险。

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence.

机构信息

Computational Engineering Division, Lawrence Livermore National Laboratory, Livermore, CA 94550 USA.

The MITRE Corporation, McLean, VA 22102 USA.

出版信息

Sci Rep. 2017 Mar 20;7:44499. doi: 10.1038/srep44499.

DOI:10.1038/srep44499
PMID:28317835
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5357958/
Abstract

Increased interconnection between critical infrastructure networks, such as electric power and communications systems, has important implications for infrastructure reliability and security. Others have shown that increased coupling between networks that are vulnerable to internetwork cascading failures can increase vulnerability. However, the mechanisms of cascading in these models differ from those in real systems and such models disregard new functions enabled by coupling, such as intelligent control during a cascade. This paper compares the robustness of simple topological network models to models that more accurately reflect the dynamics of cascading in a particular case of coupled infrastructures. First, we compare a topological contagion model to a power grid model. Second, we compare a percolation model of internetwork cascading to three models of interdependent power-communication systems. In both comparisons, the more detailed models suggest substantially different conclusions, relative to the simpler topological models. In all but the most extreme case, our model of a "smart" power network coupled to a communication system suggests that increased power-communication coupling decreases vulnerability, in contrast to the percolation model. Together, these results suggest that robustness can be enhanced by interconnecting networks with complementary capabilities if modes of internetwork failure propagation are constrained.

摘要

关键基础设施网络(如电力和通信系统)之间的互联增加,对基础设施的可靠性和安全性有重要影响。其他人已经表明,容易受到网络级联故障影响的网络之间的耦合增加会增加脆弱性。然而,这些模型中的级联机制与实际系统中的机制不同,并且这些模型忽略了通过耦合实现的新功能,例如级联期间的智能控制。本文比较了简单拓扑网络模型与更准确地反映特定耦合基础设施中级联动力学的模型的稳健性。首先,我们将传染病模型与电网模型进行比较。其次,我们将互联网级联的渗流模型与三种相互依存的电力通信系统模型进行比较。在这两种比较中,相对于更简单的拓扑模型,更详细的模型得出了截然不同的结论。除了最极端的情况外,我们的智能电网与通信系统耦合模型表明,增加电力通信耦合会降低脆弱性,这与渗流模型相反。这些结果表明,如果能够限制网络间故障传播模式,通过互联具有互补能力的网络可以提高稳健性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/8e23faae48b3/srep44499-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/d0ac3b607f6d/srep44499-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/3fd308dfb8ff/srep44499-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/8b605ee9b237/srep44499-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/8412bc893b90/srep44499-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/956b9a53ae8c/srep44499-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/89e8e8981430/srep44499-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/8e23faae48b3/srep44499-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/d0ac3b607f6d/srep44499-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/3fd308dfb8ff/srep44499-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/8b605ee9b237/srep44499-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/8412bc893b90/srep44499-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/956b9a53ae8c/srep44499-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/89e8e8981430/srep44499-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1752/5357958/8e23faae48b3/srep44499-f7.jpg

相似文献

1
Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence.通过增加基础设施网络的相互依存关系来降低级联故障风险。
Sci Rep. 2017 Mar 20;7:44499. doi: 10.1038/srep44499.
2
A complex network theory analytical approach to power system cascading failure-From a cyber-physical perspective.一种基于网络物理视角的电力系统连锁故障复杂网络理论分析方法。
Chaos. 2019 May;29(5):053111. doi: 10.1063/1.5092629.
3
Influence of Different Coupling Modes on the Robustness of Smart Grid under Targeted Attack.不同耦合模式对目标攻击下智能电网鲁棒性的影响。
Sensors (Basel). 2018 May 24;18(6):1699. doi: 10.3390/s18061699.
4
The "weak" interdependence of infrastructure systems produces mixed percolation transitions in multilayer networks.基础设施系统的“弱”关联性导致多层网络中出现混合渗流相变。
Sci Rep. 2018 Feb 1;8(1):2111. doi: 10.1038/s41598-018-20019-7.
5
The Vulnerability of the Power Grid Structure: A System Analysis Based on Complex Network Theory.电网结构的脆弱性:基于复杂网络理论的系统分析。
Sensors (Basel). 2021 Oct 26;21(21):7097. doi: 10.3390/s21217097.
6
Analysis on Cascading Failures of Directed-Undirected Interdependent Networks with Different Coupling Patterns.不同耦合模式下有向-无向相互依存网络的级联故障分析
Entropy (Basel). 2023 Mar 8;25(3):471. doi: 10.3390/e25030471.
7
Universal behavior of cascading failures in interdependent networks.**译文**:**相互依存网络中的级联故障的普遍行为**。
Proc Natl Acad Sci U S A. 2019 Nov 5;116(45):22452-22457. doi: 10.1073/pnas.1904421116. Epub 2019 Oct 17.
8
Cascading failures in interdependent systems under a flow redistribution model.在流量再分配模型下的相依系统中的级联失效。
Phys Rev E. 2018 Feb;97(2-1):022307. doi: 10.1103/PhysRevE.97.022307.
9
Optimization of cascade-resilient electrical infrastructures and its validation by power flow modeling.级联弹性电力基础设施的优化及其通过潮流建模的验证。
Risk Anal. 2015 Apr;35(4):594-607. doi: 10.1111/risa.12396. Epub 2015 Apr 30.
10
Analysis of Vulnerability on Weighted Power Networks under Line Breakdowns.线路故障下加权电力网络的脆弱性分析
Entropy (Basel). 2022 Oct 11;24(10):1449. doi: 10.3390/e24101449.

引用本文的文献

1
Interdependence of social-ecological-technological systems in Phoenix, Arizona: consequences of an extreme precipitation event.亚利桑那州凤凰城社会 - 生态 - 技术系统的相互依存关系:一场极端降水事件的后果
J Infrastruct Preserv Resil. 2023;4(1):19. doi: 10.1186/s43065-023-00085-6. Epub 2023 Aug 18.
2
Measuring accessibility to public services and infrastructure criticality for disasters risk management.测量公共服务的可达性和基础设施对灾害风险管理的关键程度。
Sci Rep. 2023 Jan 28;13(1):1569. doi: 10.1038/s41598-023-28460-z.
3
Recovery coupling in multilayer networks.

本文引用的文献

1
Does size matter?尺寸重要吗?
Chaos. 2014 Jun;24(2):023104. doi: 10.1063/1.4868393.
2
Abruptness of cascade failures in power grids.电网级联故障的突然性。
Sci Rep. 2014 Jan 15;4:3694. doi: 10.1038/srep03694.
3
Cascading failures in spatially-embedded random networks.空间嵌入随机网络中的级联失效。
多层网络中的恢复耦合。
Nat Commun. 2022 Feb 17;13(1):955. doi: 10.1038/s41467-022-28379-5.
4
Hunting for vital nodes in complex networks using local information.利用局部信息在复杂网络中寻找关键节点。
Sci Rep. 2021 Apr 28;11(1):9190. doi: 10.1038/s41598-021-88692-9.
5
A scoping review of internal hospital crises and disasters in the Netherlands, 2000-2020.2000年至2020年荷兰医院内部危机与灾难的范围综述。
PLoS One. 2021 Apr 26;16(4):e0250551. doi: 10.1371/journal.pone.0250551. eCollection 2021.
6
Symmetries and cluster synchronization in multilayer networks.多层网络中的对称和簇同步。
Nat Commun. 2020 Jun 23;11(1):3179. doi: 10.1038/s41467-020-16343-0.
7
The key player problem in complex oscillator networks and electric power grids: Resistance centralities identify local vulnerabilities.复杂振子网络和电网中的关键节点问题:电阻中心性识别局部脆弱性。
Sci Adv. 2019 Nov 22;5(11):eaaw8359. doi: 10.1126/sciadv.aaw8359. eCollection 2019 Nov.
8
Sentinel plants as programmable processing units: insights from a multidisciplinary perspective about stress memory and plant signaling and their relevance at community level.作为可编程处理单元的哨兵植物:多学科视角下关于胁迫记忆、植物信号传导及其在群落水平上相关性的见解。
Plant Signal Behav. 2018;13(10):e1526001. doi: 10.1080/15592324.2018.1526001. Epub 2018 Sep 27.
9
Enhancing robustness of interdependent network under recovery based on a two-layer-protection strategy.基于双层保护策略提升恢复过程中相互依存网络的鲁棒性。
Sci Rep. 2017 Oct 6;7(1):12753. doi: 10.1038/s41598-017-13063-2.
10
Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows.具有分布式流的空间嵌入式网络中级联过载故障的可预测性限制
Sci Rep. 2017 Sep 15;7(1):11729. doi: 10.1038/s41598-017-11765-1.
PLoS One. 2014 Jan 6;9(1):e84563. doi: 10.1371/journal.pone.0084563. eCollection 2014.
4
Transdisciplinary electric power grid science.跨学科电网科学
Proc Natl Acad Sci U S A. 2013 Jul 23;110(30):12159. doi: 10.1073/pnas.1309151110.
5
Phase transitions in supercritical explosive percolation.超临界爆炸渗流中的相变。
Phys Rev E Stat Nonlin Soft Matter Phys. 2013 May;87(5):052130. doi: 10.1103/PhysRevE.87.052130. Epub 2013 May 24.
6
Towards designing robust coupled networks.朝着设计稳健的耦合网络迈进。
Sci Rep. 2013;3:1969. doi: 10.1038/srep01969.
7
Robustness of a network formed by n interdependent networks with a one-to-one correspondence of dependent nodes.由n个相互依存网络形成的网络的稳健性,其中依存节点一一对应。
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Jun;85(6 Pt 2):066134. doi: 10.1103/PhysRevE.85.066134. Epub 2012 Jun 29.
8
Cascading failures in interdependent lattice networks: the critical role of the length of dependency links.相依晶格网络中的级联故障:依赖链路长度的关键作用。
Phys Rev Lett. 2012 Jun 1;108(22):228702. doi: 10.1103/PhysRevLett.108.228702. Epub 2012 May 31.
9
Suppressing cascades of load in interdependent networks.抑制相依网络中的负载级联。
Proc Natl Acad Sci U S A. 2012 Mar 20;109(12):E680-9. doi: 10.1073/pnas.1110586109. Epub 2012 Feb 21.
10
Robustness of a network of networks.网络的稳健性。
Phys Rev Lett. 2011 Nov 4;107(19):195701. doi: 10.1103/PhysRevLett.107.195701.