5,359 research outputs found
Power grids vulnerability: a complex network approach
Power grids exhibit patterns of reaction to outages similar to complex
networks. Blackout sequences follow power laws, as complex systems operating
near a critical point. Here, the tolerance of electric power grids to both
accidental and malicious outages is analyzed in the framework of complex
network theory. In particular, the quantity known as efficiency is modified by
introducing a new concept of distance between nodes. As a result, a new
parameter called net-ability is proposed to evaluate the performance of power
grids. A comparison between efficiency and net-ability is provided by
estimating the vulnerability of sample networks, in terms of both the metrics.Comment: 16 pages, 3 figures. Figure 2 and table II modified. Typos corrected.
Version accepted for publication in Chao
Network hierarchy evolution and system vulnerability in power grids
(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The seldom addressed network hierarchy property and its relationship with vulnerability analysis for power transmission grids from a complex-systems point of view are given in this paper. We analyze and compare the evolution of network hierarchy for the dynamic vulnerability evaluation of four different power transmission grids of real cases. Several meaningful results suggest that the vulnerability of power grids can be assessed by means of a network hierarchy evolution analysis. First, the network hierarchy evolution may be used as a novel measurement to quantify the robustness of power grids. Second, an antipyramidal structure appears in the most robust network when quantifying cascading failures by the proposed hierarchy metric. Furthermore, the analysis results are also validated and proved by empirical reliability data. We show that our proposed hierarchy evolution analysis methodology could be used to assess the vulnerability of power grids or even other networks from a complex-systems point of view.Peer ReviewedPostprint (author's final draft
Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependency
Increased coupling between critical infrastructure networks, such as power
and communication systems, will have important implications for the reliability
and security of these systems. To understand the effects of power-communication
coupling, several have studied interdependent network models and reported that
increased coupling can increase system vulnerability. However, these results
come from models that have substantially different mechanisms of cascading,
relative to those found in actual power and communication networks. This paper
reports on two sets of experiments that compare the network vulnerability
implications resulting from simple topological models and 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 shows a much higher level of
vulnerability, relative to the contagion model. Second, we compare a model of
topological cascades in coupled networks to three different physics-based
models of power grids coupled to communication networks. Again, the more
accurate models suggest very different conclusions. 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 coupled topological model, in which zero
coupling is optimal. Finally, an extreme case in which communication failures
immediately cause grid failures, suggests that if systems are poorly designed,
increased coupling can be harmful. Together these results suggest design
strategies for reducing the risk of cascades in interdependent infrastructure
systems
Stochastic Model for Power Grid Dynamics
We introduce a stochastic model that describes the quasi-static dynamics of
an electric transmission network under perturbations introduced by random load
fluctuations, random removing of system components from service, random repair
times for the failed components, and random response times to implement optimal
system corrections for removing line overloads in a damaged or stressed
transmission network. We use a linear approximation to the network flow
equations and apply linear programming techniques that optimize the dispatching
of generators and loads in order to eliminate the network overloads associated
with a damaged system. We also provide a simple model for the operator's
response to various contingency events that is not always optimal due to either
failure of the state estimation system or due to the incorrect subjective
assessment of the severity associated with these events. This further allows us
to use a game theoretic framework for casting the optimization of the
operator's response into the choice of the optimal strategy which minimizes the
operating cost. We use a simple strategy space which is the degree of tolerance
to line overloads and which is an automatic control (optimization) parameter
that can be adjusted to trade off automatic load shed without propagating
cascades versus reduced load shed and an increased risk of propagating
cascades. The tolerance parameter is chosen to describes a smooth transition
from a risk averse to a risk taken strategy...Comment: framework for a system-level analysis of the power grid from the
viewpoint of complex network
Topological Performance Measures as Surrogates for Physical Flow Models for Risk and Vulnerability Analysis for Electric Power Systems
Critical infrastructure systems must be both robust and resilient in order to
ensure the functioning of society. To improve the performance of such systems,
we often use risk and vulnerability analysis to find and address system
weaknesses. A critical component of such analyses is the ability to accurately
determine the negative consequences of various types of failures in the system.
Numerous mathematical and simulation models exist which can be used to this
end. However, there are relatively few studies comparing the implications of
using different modeling approaches in the context of comprehensive risk
analysis of critical infrastructures. Thus in this paper, we suggest a
classification of these models, which span from simple topologically-oriented
models to advanced physical flow-based models. Here, we focus on electric power
systems and present a study aimed at understanding the tradeoffs between
simplicity and fidelity in models used in the context of risk analysis.
Specifically, the purpose of this paper is to compare performances measures
achieved with a spectrum of approaches typically used for risk and
vulnerability analysis of electric power systems and evaluate if more
simplified topological measures can be combined using statistical methods to be
used as a surrogate for physical flow models. The results of our work provide
guidance as to appropriate models or combination of models to use when
analyzing large-scale critical infrastructure systems, where simulation times
quickly become insurmountable when using more advanced models, severely
limiting the extent of analyses that can be performed
The interplay of network structure and dispatch solutions in power grid cascading failures
For a given minimum cost of the electricity dispatch, multiple equivalent dispatch solutions may exist. We explore the sensitivity of networks to these dispatch solutions and their impact on the vulnerability of the network to cascading failure blackouts. It is shown that, depending on the heterogeneity of the network structure, the blackout statistics can be sensitive to the dispatch solution chosen, with the clustering coefficient of the network being a key ingredient. We also investigate mechanisms or configurations that decrease discrepancies that can occur between the different dispatch solutions
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