Title: Correlating empirical data and extended topological measures in power grid networks

Authors: Lingen Luo; Marti Rosas-Casals

Addresses: Dipartimento Energia, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy ' Sustainability Measurement and Modelling Lab, Universitat Politècnica de Catalunya – Barcelona Tech, 1, Colom st., 08222 Terrassa, Spain

Abstract: Power grids are considered complex networks. Their structure and dynamics have been thoroughly studied and many topological measures have been used to classify them, evaluate their behaviour or model their response to malfunctions. Results have been theoretical and correlations between real dynamical behaviour (i.e., major events) and structural measures have not yet been found. New electrically modified topological measures have been recently used to quantify the ability of a network in sustaining its functions. Here, we present a first attempt to correlate these new measures with real malfunction data for some European power transmission grids. Similar behaviour is found, in terms of robustness to selected attacks to buses, between different networks. These behaviours can be correlated with similar probability distributions of major events, identifying similar dynamical response among topologically similar grids. This would raise hopes in finding a more meaningful linkage between structural measures and the real dynamical output of a grid.

Keywords: complex networks; graph theory; electrical betweenness; entropy degree; topological measures; fat-tailed distribution; maximal information-based statistics; KS test; Kolmogorov-Smirnov; empirical data; power grids; power networks; malfunction data; European power transmission; robustness; bus attacks; dynamic response; network security; critical infrastructures.

DOI: 10.1504/IJCIS.2015.067396

International Journal of Critical Infrastructures, 2015 Vol.11 No.1, pp.82 - 96

Received: 03 Jul 2013
Accepted: 03 Jul 2013
Published online: 25 Apr 2015 *

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