Spatial correlation analysis of cascading failures: Congestions and Blackouts

Li Daqing; Jiang Yinan; Kang Rui; Shlomo Havlin

doi:10.1038/srep05381

Spatial correlation analysis of cascading failures: Congestions and Blackouts

Li Daqing, Jiang Yinan, Kang Rui, Shlomo Havlin

Department of Physics

Research output: Contribution to journal › Article › peer-review

123 Scopus citations

Abstract

Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs.

Original language	English
Article number	5381
Journal	Scientific Reports
Volume	4
DOIs	https://doi.org/10.1038/srep05381
State	Published - 20 Jun 2014

Bibliographical note

Funding Information:
We thank the support from National Natural Science Foundation of China (Grants No. 61104144). We thank Wang Y.P., Lu G.Q. and Gao L. for their assistance with the traffic and blackout datasets, respectively. S.H. thanks DTRA, ONR, the LINC and the Multiplex (No. 317532) EU projects, the DFG, and the Israel Science Foundation for support.

Funding

We thank the support from National Natural Science Foundation of China (Grants No. 61104144). We thank Wang Y.P., Lu G.Q. and Gao L. for their assistance with the traffic and blackout datasets, respectively. S.H. thanks DTRA, ONR, the LINC and the Multiplex (No. 317532) EU projects, the DFG, and the Israel Science Foundation for support.

Funders	Funder number
LINC
Office of Naval Research
Defense Threat Reduction Agency
Seventh Framework Programme	317532
Deutsche Forschungsgemeinschaft
National Natural Science Foundation of China	61104144
Israel Science Foundation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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title = "Spatial correlation analysis of cascading failures: Congestions and Blackouts",

abstract = "Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs.",

author = "Li Daqing and Jiang Yinan and Kang Rui and Shlomo Havlin",

note = "Funding Information: We thank the support from National Natural Science Foundation of China (Grants No. 61104144). We thank Wang Y.P., Lu G.Q. and Gao L. for their assistance with the traffic and blackout datasets, respectively. S.H. thanks DTRA, ONR, the LINC and the Multiplex (No. 317532) EU projects, the DFG, and the Israel Science Foundation for support.",

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N1 - Funding Information: We thank the support from National Natural Science Foundation of China (Grants No. 61104144). We thank Wang Y.P., Lu G.Q. and Gao L. for their assistance with the traffic and blackout datasets, respectively. S.H. thanks DTRA, ONR, the LINC and the Multiplex (No. 317532) EU projects, the DFG, and the Israel Science Foundation for support.

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N2 - Cascading failures have become major threats to network robustness due to their potential catastrophic consequences, where local perturbations can induce global propagation of failures. Unlike failures spreading via direct contacts due to structural interdependencies, overload failures usually propagate through collective interactions among system components. Despite the critical need in developing protection or mitigation strategies in networks such as power grids and transportation, the propagation behavior of cascading failures is essentially unknown. Here we find by analyzing our collected data that jams in city traffic and faults in power grid are spatially long-range correlated with correlations decaying slowly with distance. Moreover, we find in the daily traffic, that the correlation length increases dramatically and reaches maximum, when morning or evening rush hour is approaching. Our study can impact all efforts towards improving actively system resilience ranging from evaluation of design schemes, development of protection strategies to implementation of mitigation programs.

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Spatial correlation analysis of cascading failures: Congestions and Blackouts

Abstract

Bibliographical note

Funding

UN SDGs

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