Correlating empirical data and extended topological measures in power grid networks. (1st January 2015)

• Record Type: Journal Article
• Authors: Luo, Lingen; Rosas–Casals, Marti
• Is Part Of: International journal of critical infrastructures. Volume 11:Number 1(2015)
• Page Start: 82
• Page End: 96
• Publication Date: 2015-01-01
• Subjects: 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; Infrastructure (Economics) -- Security measures -- Periodicals; Risk assessment -- Periodicals; Emergency management -- Periodicals; 363.05
• DOI: 10.1504/IJCIS.2015.067396
• Languages: English
• ISSNs: 1475-3219

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.