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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
From Social Simulation to Integrative System Design
As the recent financial crisis showed, today there is a strong need to gain
"ecological perspective" of all relevant interactions in
socio-economic-techno-environmental systems. For this, we suggested to set-up a
network of Centers for integrative systems design, which shall be able to run
all potentially relevant scenarios, identify causality chains, explore feedback
and cascading effects for a number of model variants, and determine the
reliability of their implications (given the validity of the underlying
models). They will be able to detect possible negative side effect of policy
decisions, before they occur. The Centers belonging to this network of
Integrative Systems Design Centers would be focused on a particular field, but
they would be part of an attempt to eventually cover all relevant areas of
society and economy and integrate them within a "Living Earth Simulator". The
results of all research activities of such Centers would be turned into
informative input for political Decision Arenas. For example, Crisis
Observatories (for financial instabilities, shortages of resources,
environmental change, conflict, spreading of diseases, etc.) would be connected
with such Decision Arenas for the purpose of visualization, in order to make
complex interdependencies understandable to scientists, decision-makers, and
the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c
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