Empirical framework for identification of the most harmful malicious attacks on a smart grid

被引:0
作者
Aiman J. Albarakati
Marwan Bikdash
机构
[1] Majmaah University,College of Computer and Information Science
[2] North Carolina A&T state University,Computational Data Science and Engineering
来源
Applied Network Science | / 7卷
关键词
Vulnerability assessment; Graph theory; Powergrid; Centrality measures; Matpower;
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摘要
The aim of this paper is the identification of the most harmful malicious attacks in a smart grid with basis on the removal of buses in a particular sequence. For that, we define the Electrical Most Damaging Element (EMDE) and the Iterated Centrality Measure (ICM). The EMDE is the element that leads to the largest unsatisfied load increase after removed, in the current state of the smart grid. The ICM is a meaningful scaled centrality for iterated attacks. Attack strategies such as the IEMDE (Iterated Electrical Most Damaging Element) and the Iterated Most Central Element (IMCE) are proposed as references for evaluating the impact of failure sequences by comparison. For each fault strategy approach, the vulnerability curves as well as a scalability analysis are presented. It is demonstrated that the IEMDE approximated the N-k-ε\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N-k-\varepsilon$$\end{document} algorithm, but with reduced computational expense. Furthermore, the IMCE approach provided an efficient fault profile close to the performance of the IEMDE. Although this framework is applied in this paper to failures in buses, it can similarly be applied to other elements. Future research will be focused in applying these concepts to transmission lines.
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  • [11] Bompard E(2012)European power grid reliability indicators, what do they really tell? Electr Power Syst Res 90 79-2096
  • [12] Carbone A(2012)Suppressing cascades of load in interdependent networks Proc Natl Acad Sci 109 E680-79
  • [13] Xue F(2014)Contingency-risk informed power system design IEEE Trans Power Syst 29 2087-9265
  • [14] Arroyo JM(2013)Grid vulnerability analysis based on scale-free graphs versus power flow models Electr Power Syst Res 101 71-469
  • [15] Galiana FD(2015)A critical review of robustness in power grids using complex networks concepts Energies 8 9211-424
  • [16] Arroyo JM(2020)A novel approach in strategic planning of power networks against physical attacks Electr Power Syst Res 180 106140-27
  • [17] Alguacil N(2004)Energy infrastructure and security Annu Rev Environ Resour 29 421-84
  • [18] Carrion M(2017)Modeling and vulnerability analysis of cyber-physical power systems considering network topology and power flow properties Energies 10 87-107
  • [19] Bilis EI(2015)Reliability optimization of electrical distribution systems using internal loops to minimize energy not-supplied (ENS) J Appl Res Technol 13 416-22
  • [20] Kroger W(2016)Cyber-physical attacks and defences in the smart grid: a survey IET Cyber-Phys Syst Theory Appl 1 13-154