Simulation of Cascading Outages in (Inter)-Dependent Services and Estimate of Their Societal Consequences
We present RecSIM, a specific application which is part of the CIPCast tool, a Decision Support System (DSS) for risk analysis of (inter)-dependent Critical Infrastructures (CI) under development within the EU FP7 CIPRNet Project. Electrical and the telecommunication networks play a central role in systems of CI and are also strongly inter-dependent: the latter allows tele-control operations on the former which, in turn, supplies energy to the latter. Services outages of those CI can generate cascading effects also on other systems, thus producing large societal consequences. The RecSIM tool is a discrete-time simulator able to model the dependencies between the electric and the telecommunication systems, to simulate the cascading effects in the two networks and to reproduce the results of the actions taken by operators to reconfigure the electrical network. Starting from the prediction of damages on the network topology, RecSIM reproduces the whole crisis and estimates the resulting outages (outage start and outage end) in all the involved CI elements. RecSIM, moreover, through the Consequence Analysis module, estimates the effects of the degradation (or the complete loss) of the electric and the telecommunication services, via the estimate of specific indices useful to assess the severity of the crisis in terms of its societal impact.
KeywordsCritical infrastructures Simulator Electrical network Telecommunication network Wealth index
This work was developed from the FP7 Network of Excellence CIPRNet, which is being partly funded by the European Commission under grant number FP7-312450-CIPRNet. The European Commissions support is gratefully acknowledged.
- 1.Di Pietro, A., Lavalle, L., Pollino, M., Rosato, V., Tofani, A.: Supporting decision makers in crisis scenarios involving interdependent physical systems. The International Emergency Management Society (TIEMS) (2015)Google Scholar
- 2.Smits, J., Steendijk, R.: The International Wealth Index, NiCE Working Paper 12-107, Nijmegen Center for Economics (NiCE) Institute for Management Research, Radboud University, Nijmegen (The Netherlands), December 2013Google Scholar
- 3.Leontief, W.: Input-output analysis. In: Input- Output Economics, p. 1940 (1986)Google Scholar
- 4.Di Pietro, A., Lavalle, L., La Porta, L., Pollino, M., Tofani, A., Rosato, V.: Design of DSS for supporting preparedness to and management of anomalous situations in complex scenarios. In: Setola, R., Rosato, V., Kyriakides, E., Rome, E. (eds.) Managing the Complexity of Critical Infrastructures. SSDC, vol. 90, pp. 195–232. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-51043-9_9 CrossRefGoogle Scholar
- 5.Italian National Institute of Statistics. http://www.istat.it/it/prodotti/microdati