In order to meet power demands in a sustainable way, power grids are gradually being adjusted to fit into a smart grid paradigm. A common problem in this kind of transition is to identify locations where it is most beneficial to invest in distributed generation. In order to assist in such a decision, we work on a graph model of a regional power grid. We apply optimization strategies on power flows, and verify the current degree of self-sufficiency of the network, with special reference to the effect of natural variations in wind-based production. We propose a method to assess collateral damage to the network resulting from a localized failure, and proceed to perform complex network analysis on multiple instances of the network, looking for correlations between estimated damages and betweenness centrality indices, with the purpose of attempting to determine which model is best suited to predict features of our network.

Evaluating complex network indices for vulnerability analysis of a territorial power grid

FENU, GIANNI;PAU, PIER LUIGI
2015-01-01

Abstract

In order to meet power demands in a sustainable way, power grids are gradually being adjusted to fit into a smart grid paradigm. A common problem in this kind of transition is to identify locations where it is most beneficial to invest in distributed generation. In order to assist in such a decision, we work on a graph model of a regional power grid. We apply optimization strategies on power flows, and verify the current degree of self-sufficiency of the network, with special reference to the effect of natural variations in wind-based production. We propose a method to assess collateral damage to the network resulting from a localized failure, and proceed to perform complex network analysis on multiple instances of the network, looking for correlations between estimated damages and betweenness centrality indices, with the purpose of attempting to determine which model is best suited to predict features of our network.
2015
Complex networks; Optimization; Power grids; Smart grids; Vulnerability analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/60895
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