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  School of Mathematical Sciences, Queen Mary, University of London
School of Mathematical Sciences, Queen Mary, University of London
 
Project Summary
FP6

The scope of the project concerns the mathematical methods required to understand the dynamics of the network of networks that comprise Europe’s critical infrastructure; concentrating primarily on energy supply, emergency response systems and subsidiary key infrastructures (such as transport) that are either directly dependent on them, or are critically relied for in times of crises.  

Man-made interdependent infrastructures are strategic assets and commodities, whose secure, reliable and affordable supply are essential to Europe’s socio-economic development and stability. Europe is undergoing a radical conversion of the operability in many of its critical physical infrastructure systems (electricity, gas, water, sewage and transport). This is being driven by market deregulation and unbundling of the European energy and utilities sectors, promoted by a suite of policies and EU Directives.

In the energy sector, concerns regarding the vulnerabilities associated with the increasing dependency of the EU on imported hydrocarbons (particularly gas for power generation), the infrastructures for transportation, and, in view of major blackout events, the electricity grid systems, are the subject of serious attention by policy makers. Recently, the heightened sensitivities to the threat of terrorist attacks have raised additional major concerns regarding the security of these, so-called, critical infrastructures. However, even though serious, maliciously initiated, disruptions are and have been possible, records would seem to indicate that major regional, or nation-wide, blackouts and service disruptions are often the result of chance events perturbing systems that are highly congested, of low-redundancy, and at the limit of their operational limits.

The threats to these networks include: supply side geo-politics and market instability; malicious acts (terrorism, crime); natural processes and calamities (extreme weather, seismic activity, flooding) and impacts of climate change. Technological factors include ageing infrastructures (particularly outside of the EU), accidents and disasters on land and sea, and increasingly, electricity blackouts resulting from complex grid interconnections.

Such concerns transcend the interests of individual Member States. However, at present, there is lacking a knowledge and understanding of the macroscopic dynamic behaviour of interconnected transport infrastructures. Even though it is well understood how the individual systems that make them up operate, their interdependencies, key vulnerabilities, and the consequences of a major disruption at critical nodes of the infrastructures are still far from being well understood.

In addition to the day-to-day planning, both long-term and emergency planning strategies increasingly require an understanding of the underlying dynamic response of such complex systems to external stimuli. By dynamic response we mean the macroscopic changes in the topological and structural stability of the system at a macro-scale that arise in network interconnectivity as a result of a wide range of stimuli. These stimuli may be brought about by natural or man-made causes at both long and short time scales. For example, un-damped frequency oscillations in electricity grids, originate locally and may propagate very quickly over thousands of kilometres; long-term planning strategies such as road network renewal or the proposals for numerous large offshore wind-farms are currently the subject of much fervent discussion between network utilities owners and users and society at large.

Arguments for and against the reliability and resilience of these complex systems, —as proposed by opposing group interests— are ricocheting through the halls of the corporate and political world. Often, the views are polarized, and the arguments —for and against— rely on postulations which, so far, have not been rigorously analysed using the mathematical methods which could best suit such a complex problem.

In tandem with these techno-economic concerns, certain governmental bodies —working alongside other national authorities— must cooperate closely with network owners so as to ensure minimum services of these networks in times of major disruptions. In order to manage the complexity overall and target the network elements most at risk, this too, requires a macroscopic vision of how these interconnected systems interact.

 
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