Electric power grid vulnerability analysis based on complex network

Pao Yue-kong Library Electronic Theses Database

Electric power grid vulnerability analysis based on complex network


Author: Di, Li
Title: Electric power grid vulnerability analysis based on complex network
Degree: M.Sc.
Year: 2011
Subject: Electric power systems
Electric power transmission
Electric networks
Hong Kong Polytechnic University -- Dissertations
Department: Dept. of Electronic and Information Engineering
Pages: viii, 77 leaves : ill. (chiefly col.) ; 30 cm.
InnoPac Record: http://library.polyu.edu.hk/record=b2445339
URI: http://theses.lib.polyu.edu.hk/handle/200/6138
Abstract: Since the first power plant was built in 1881, continuous development and improvement have been made to enhance the electrical power industry. Engineers have always been deriving effective methods to improve the safety and quality of electricity supply, and to ensure the reliability of power delivery. Intensive research has been performed before to maintain the reliability of the power system, which involves identifying the vulnerability of the power system. However, quite a lot of those works only deal with a specific local area, rather than addressing the global system. To address the global problem, a complex network-based method, which is called betweenness centrality analysis, will be presented in this dissertation to identify the vulnerable parts of a given power network and to derive an effective method to eliminate the vulnerability problem. In order to identify the kind of model the power network belongs to, three models (i.e., random network, small-world network, scale-free network) will be used to compare with the standard testing model, which is the IEEE series bus system. Three attack scenarios based on random attack, node degree, node betweenness, will be applied on each of these networks to identify the most vulnerable model as well as the most robust one. Simulations will be conducted on MATLAB to provide reliable information regarding network safety and robustness.

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