Use of Network Analysis to Assess the Vulnerability of an Electrical Supply Network

Abstract eng:
This paper presents the results of a network analysis of the UK’s electrical distribution network. A mathematical network model was developed which could simulate the network’s response to the effect of natural disaster. This model was then used to calculate the topological properties of the network and simulate the effects of a disaster by randomly removing links and nodes from the model. The model was constructed using a map of the transmission system of the National Grid of the United Kingdom. The nodes in the model represented the power stations and substations and the links the transmission lines. The final model representing the network contained 55 large power stations, 169 substations and 313. Topological properties, such as the clustering coefficient, of the network were calculated. In addition to calculating network properties, an algorithm was developed which independently removed links at random from the network. 2000 simulations were conducted to assess the vulnerability of the network. The results of the study show that the UK’s electrical distribution network has a clustering coefficient of 0.14, which is slightly higher than the value of 0.1 calculated by Watts P& Strogatz (1998) for the North America power grid. This suggests the UK’s electrical distribution network is likely to be more robust. Also, the average number of links that can be removed before failure is estimated to be 6, implying that on average, 6 links (high voltage transmission lines) would have to fail simultaneously or shortly after one another before a community or region loses electricity supply. As a result of this analysis it is proposed that by adding several critical links to the network its robustness can be significantly increased and the vulnerability of certain nodes can be greatly reduced.

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