Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Computational Engineering Division
The MITRE Corporation, McLean, VA (United States)
The MITRE Corporation, McLean, VA (United States); Univ. of Vermont, Burlington, VT (United States). Vermont Complex Systems Center
Univ. of Vermont, Burlington, VT (United States). Vermont Complex Systems Center; Univ. of Vermont, Burlington, VT (United States). Dept. of Mathematics & Statistics
Univ. of Vermont, Burlington, VT (United States). Vermont Complex Systems Center; Univ. of Vermont, Burlington, VT (United States). Dept. of Electrical and Biomedical Engineering
Increased coupling between critical infrastructure networks, such as power and communication systems, has important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several researchers have studied models of interdependent networks and reported that increased coupling can increase vulnerability. However, these conclusions come largely from models that have substantially different mechanisms of cascading failure, relative to those found in actual power and communication networks, and that do not capture the benefits of connecting systems with complementary capabilities. In order to understand the importance of these details, this paper compares network vulnerability in simple topological models and in models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid model shows a higher level of vulnerability, relative to the contagion model. Second, we compare a percolation model of topological cascading in coupled networks to three different models of power networks coupled to communication systems. Again, the more accurate models suggest very different conclusions than the percolation model. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the percolation model, in which zero coupling is optimal. Only in an extreme case, in which communication failures immediately cause grid failures, did we find that increased coupling can be harmful. Together, these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems.
Korkali, Mert, Veneman, Jason G., Tivnan, Brian F., Bagrow, James P., & Hines, Paul D. H. (2017). Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence. Scientific Reports, 7. https://doi.org/10.1038/srep44499
@article{osti_1349000,
author = {Korkali, Mert and Veneman, Jason G. and Tivnan, Brian F. and Bagrow, James P. and Hines, Paul D. H.},
title = {Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependence},
annote = {Increased coupling between critical infrastructure networks, such as power and communication systems, has important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several researchers have studied models of interdependent networks and reported that increased coupling can increase vulnerability. However, these conclusions come largely from models that have substantially different mechanisms of cascading failure, relative to those found in actual power and communication networks, and that do not capture the benefits of connecting systems with complementary capabilities. In order to understand the importance of these details, this paper compares network vulnerability in simple topological models and in models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid model shows a higher level of vulnerability, relative to the contagion model. Second, we compare a percolation model of topological cascading in coupled networks to three different models of power networks coupled to communication systems. Again, the more accurate models suggest very different conclusions than the percolation model. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the percolation model, in which zero coupling is optimal. Only in an extreme case, in which communication failures immediately cause grid failures, did we find that increased coupling can be harmful. Together, these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems.},
doi = {10.1038/srep44499},
url = {https://www.osti.gov/biblio/1349000},
journal = {Scientific Reports},
issn = {ISSN 2045-2322},
volume = {7},
place = {United States},
publisher = {Nature Publishing Group},
year = {2017},
month = {03}}