Details of Grant 

EPSRC Reference:	EP/H04812X/1
Title:	RAVEN: Resilience, Adaptability and Vulnerability of complex Energy Networks
Principal Investigator:	Arrowsmith, Professor DK
Other Investigators:	Mondragon, Dr RJ Just, Dr W
Researcher Co-Investigators:	Dr RP Ribeiro Ferreira de Carvalho
Project Partners:
Department:	Sch of Mathematical Sciences
Organisation:	Queen Mary University of London
Scheme:	Standard Research
Starts:	14 May 2010	Ends:	13 May 2013	Value (£):	355,446
EPSRC Research Topic Classifications:	Non-linear Systems Mathematics Sustainable Energy Networks
EPSRC Industrial Sector Classifications:	Energy
Related Grants:
Panel History:	Panel Date Panel Name Outcome 04 Mar 2010 Mathematics Prioritisation Panel Announced
Summary on Grant Application Form
Energy infrastructure has gone through unprecedented change in recent decades and has resulted in the emergence of enormous networks that transcend national borders and even continental shores. There is, thus, an urgent need to generate more systematic knowledge on these complex systems, if one is to succeed in adequately handling the many threats and vulnerabilities. The project RAVEN aims at capturing essential measures, parameters and qualitative behaviours which may help us to gain insights into the limits of operation of these critical infrastructure networks, as well as to design the 'smart' grids of the future in a robust way. To accomplish this, we have identified five major problems which are both timely and solvable during the duration of the project.Problem 1. Energy networks have evolved under the pressure to minimize local rather than global failures. However, little is known about how this local optimization has influenced the vulnerability of energy infrastructures at the scale of continents. We will develop graph theoretical measures to characterise the vulnerability of European cities to intentional attacks, based on both current and future planned gas and electricity networks.Problem 2. The impact of infrastructure component failures and their severity on interconnected networks can be exacerbated and are generally much higher and more difficult to foresee, compared with failures confined to single infrastructures. We will approach this problem from two angles. On one hand, we will develop mathematical measures to characterise the increased risk for the interconnected real-world European gas and electricity networks. On the other hand, we will attempt to introduce a model control network which oversees the real world infrastructure networks, and extract measures of its vulnerability and redundancy.Problem 3. Although the UK has been self-sufficient so far, its energy needs are changing rapidly. In particular, 30 years of intense domestic exploitation of natural gas have resulted in the need for ever-increasing imports. Therefore, it is clear that the switch from net exporter to large importer as well as the associated changes in the marketplace raise new issues for security of supply for the UK. These issues are particularly acute during scenarios of geo-political crises such as the Ukraine-Russian supply crisis in January 2009. Our aim here will be to characterise the role of network structure when it is based on fair allocation of flows to end consumers.Problem 4. Generally speaking, the 'Smart' Grid will be more like the Internet: exchanging information and energy among nodes for collaboration across the network resulting in a more efficient, sustainable grid and a real-time evolving energy marketplace. However, it is largely unknown how the coupling between spot price, energy availability and consumers will adapt to such real-time interaction. Our goal is to determine which parameters control the dynamics of the coupled system, since these will be the crucial measures of study in the real world.Problem 5. Over the last decade, we have accumulated considerable knowledge on the topology and flow characteristics of the electricity and gas grids from the point of view of complex networks. However, little is known about transport processes on gas pipeline networks. In parallel, the lack of geographically extended data sets has constrained analyses of flows on the power grid to the scale of nations, and a general theory of dynamical processes at the scale of continents is still elusive. To address these issues, we will analyse time series data of inputs to gas pipeline networks. We will also study further the dynamics of blackouts from cascade propagation and phase de-synchronisation on the power grid at the European scale with a particular emphasis to the relation between the UK and other European countries.
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