Modeling cascading failures in the North American power grid

By R. Kinney, Paolo Crucitti, Réka Albert, Vito Latora. 2004

715 citations recorded by the source corpus.

Abstract.The North American power grid is one of the most complex technological networks, and its interconnectivity allows both for long-distance power transmission and for the propagation of disturbances. We model the power grid using its actual topology and plausible assumptions about the load and overload of transmission substations. Our results indicate that the loss of a single substation can result in up to $25\%$ loss of transmission efficiency by triggering an overload cascade in the network. The actual transmission loss depends on the overload tolerance of the network and the connectivity of the failed substation. We systematically study the damage inflicted by the loss of single nodes, and find three universal behaviors, suggesting that $40\%$ of the transmission substations lead to cascading failures when disrupted. While the loss of a single node can inflict substantial damage, subsequent removals have only incremental effects, in agreement with the topological resilience to less than $1\%$ node loss.

Subfields: Civil and Structural Engineering, Mathematical Physics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/098105d22376a8cc9359d7f058b224ed45df1398

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In Civil and Structural Engineering

In Mathematical Physics

In Statistical and Nonlinear Physics

Citations in the corpus

Robustness and resilience of complex networks (2024, background): “…the most common approach 70 involves percolation-related metrics, such as monitoring the size of the largest connected component (LCC) and stopping the attack once it has reached a given target size, although other network metrics such as efficiency 59,71 or nestedness 50,51,72 have been used.”
False data injection attacks against state estimation in electric power grids (2009, background): “For example, an attacker can obtain the configuration of the North American power grid from the POWERmap mapping system, which contains information about every power plant, major substation, and 115-765kV power line of the North American power grid [17].”
False data injection attacks against state estimation in electric power grids (2011, methodology): “For example, an attacker can obtain the configuration of the North American power grid from the POWERmap mapping system, which contains information about every power plant, major substation, and 115-765 kV power line of the North American power grid [ 17 ].”
Network resilience (2020, background): “For North American power grids, the failure of a single substation could lead to up to 25% loss of transmission efficiency as a result of an overload cascade [633].”
Energy Theft in the Advanced Metering Infrastructure (2009, background): “For example, an adversary that attempts to cause rolling blackouts [7,8] may have a sub-goal of forging energy demand at distribution substation meters.”
Spatial Networks (2010, background): “Various studies examined the vulnerability of infrastructures such as power grids [9, 192, 288], Internet, or transportation networks [105, 210, 321] and most of these studies are not concerned with spatial aspects but rather focused on how to measure the damage and the effect of various attack stra”
The Power Grid as a Complex Network: a Survey (2011, methodology): “The authors compute three set of metrics: eﬃciency already applied in Power Grid studies [38, 57], net-ability and overload.”
Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, background): “In the analysis of the topology of these networks, it was show n that the removal of highly connected nodes (without distinguishing their types) can l ead to blackouts of certain regions of the networks [320, 321, 322].”
Characterization of complex networks: A survey of measurements (2005, background): “nd to real physical entities, such as roads and optical ﬁbers [58]. This kind of networks is called geographical or spatial networks. Other important examples of geographical networks are power grids [59, 60], airport networks [61, 62, 63], subway [64] and neural networks [65]. In geographical netwo”