Network topological notions for power systems security assessment

The identification of topological vulnerabilities is a prerequisite for the study of security analysis. This paper presents a graph-theoretic framework to detect the minimum set of transmission lines interconnecting subnetworks inside of a power network. Moreover, the framework is used to develop a...

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Autores:
Moreno-Chuquen, Ricardo
Obando Ceron, Johan Samir
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Universidad Autónoma de Occidente
Repositorio:
RED: Repositorio Educativo Digital UAO
Idioma:
eng
OAI Identifier:
oai:red.uao.edu.co:10614/11393
Acceso en línea:
http://hdl.handle.net/10614/11393
https://doi.org/10.15866/iree.v13i3.14210
Palabra clave:
Análisis de redes eléctricas
Electric network analysis
Sistemas de interconexión eléctrica
Interconnected electric utility systems
Graph theory
Network assessment
Contingency analysis
Power system security
Rights
restrictedAccess
License
Derechos Reservados - Universidad Autónoma de Occidente
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network_acronym_str REPOUAO2
network_name_str RED: Repositorio Educativo Digital UAO
repository_id_str
dc.title.eng.fl_str_mv Network topological notions for power systems security assessment
title Network topological notions for power systems security assessment
spellingShingle Network topological notions for power systems security assessment
Análisis de redes eléctricas
Electric network analysis
Sistemas de interconexión eléctrica
Interconnected electric utility systems
Graph theory
Network assessment
Contingency analysis
Power system security
title_short Network topological notions for power systems security assessment
title_full Network topological notions for power systems security assessment
title_fullStr Network topological notions for power systems security assessment
title_full_unstemmed Network topological notions for power systems security assessment
title_sort Network topological notions for power systems security assessment
dc.creator.fl_str_mv Moreno-Chuquen, Ricardo
Obando Ceron, Johan Samir
dc.contributor.author.none.fl_str_mv Moreno-Chuquen, Ricardo
Obando Ceron, Johan Samir
dc.subject.lemb.spa.fl_str_mv Análisis de redes eléctricas
topic Análisis de redes eléctricas
Electric network analysis
Sistemas de interconexión eléctrica
Interconnected electric utility systems
Graph theory
Network assessment
Contingency analysis
Power system security
dc.subject.lemb.eng.fl_str_mv Electric network analysis
dc.subject.armarc.spa.fl_str_mv Sistemas de interconexión eléctrica
dc.subject.armarc.eng.fl_str_mv Interconnected electric utility systems
dc.subject.proposal.eng.fl_str_mv Graph theory
Network assessment
Contingency analysis
Power system security
description The identification of topological vulnerabilities is a prerequisite for the study of security analysis. This paper presents a graph-theoretic framework to detect the minimum set of transmission lines interconnecting subnetworks inside of a power network. Moreover, the framework is used to develop a method to classify the criticality of substations. The approach can be used with power transfer distribution factors information to gain an insight about the power system security. Sometimes the power network exhibits high vulnerability related to critical transmission lines interconnecting critical substations from a physical point of view. The quantification of structural properties can provide meaningful information needed to assess and enhance the reliability and security of power system networks. The capabilities for the topological approach are illustrated on two large-scale networks. The proposed approach provides an effective tool for both real-time and offline environments for security analysis and control
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2019-11-05T15:24:09Z
dc.date.available.none.fl_str_mv 2019-11-05T15:24:09Z
dc.type.spa.fl_str_mv Artículo de revista
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identifier_str_mv 18276660
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https://doi.org/10.15866/iree.v13i3.14210
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.citationissue.none.fl_str_mv 3
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dc.relation.cites.eng.fl_str_mv Moreno-Chuquen, R., & Obando-Ceron, J. (2018). Network Topological Notions for Power Systems Security Assessment. International Review of Electrical Engineering (IREE), 237
dc.relation.ispartofjournal.eng.fl_str_mv International Review of Electrical Engineering
dc.relation.references.none.fl_str_mv A. J. Wood and B. F. Wollenberg, Power Generation, Operation, and Control, 3nd ed. New York, NY, USA: Wiley, 2014. http://dx.doi.org/10.1016/0140-6701(96)88715-7
Rami Reddy, B., Sujatha, P., Siva Reddy, Y., Interline Power Flow Controller (IPFC) to Improve the Voltage Stability and Contingency Analysis in Power System, (2016) International Review of Electrical Engineering (IREE), 11 (1), pp. 109-115. http://dx.doi.org/10.15866/iree.v11i1.6790
R. Albert, I. Albert, and G. L. Nakarado, Structural vulnerability of the North American power grid, Phys. Rev. E, vol. 69, pp. 1–10, Feb. 2004. http://dx.doi.org/10.1103/physreve.69.025103
S. Arianos, E. Bompard, A. Carbone, and F. Xue, Power grid vulnerability: A complex network approach, Chaos, vol. 19, no. 01199, 2009. http://dx.doi.org/10.1063/1.3077229
Y. Zhu, J. Yan, Y. Sun, and H. He, Revealing cascading failure vulnerability in power grids using risk-graph, IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 12, pp. 3274–3284, Dec. 2014. http://dx.doi.org/10.1109/tpds.2013.2295814
P. Crucitti, V. Latora, and M. Marchiori, Locating critical lines in high-voltage electrical power grids, Fluctuation Noise Lett., vol. 5, no. 2, 2005. http://dx.doi.org/10.1142/s0219477505002562
V. Latora and M. Marchiori, Vulnerability and protection of infrastructure networks, Phys. Rev. E, vol. 71, no. 015103(R), 2005. http://dx.doi.org/10.1103/physreve.71.015103 E. Bompard, D. Wu, F. Xue, Structural vulnerability of power systems: A topological approach, Electr. Power Syst. Res., vol. 81, pp. 1334–1340, 2011. http://dx.doi.org/10.1016/j.epsr.2011.01.021
A. Peiravi, R. Ildarabadi, Graph partitioning Applications in Electrical Engineering with an Emphasis on Power System Intentional Islanding, (2009) International Review of Electrical Engineering (IREE), 4 (5), pp. 914-924
T. Jiang, L. Bai, H. Jia, and F. Li, Spectral clustering-based partitioning of volt/VAR control areas in bulk power systems, IET Gener. Transm. Distrib. Vol. 11 Iss. 5, pp. 1126-1133, 2017. http://dx.doi.org/10.1049/iet-gtd.2016.0709
J. Quirós-Tortós, R. Sanchéz-García, J. Brodski, J.Bialek, and V. Terzija, Constrained spectral clustering-based methodology for intentional controlled islanding of large-scale power systems, IET Gener. Transm. Distrib. Vol. 9 Iss. 1, pp. 31-42, 2014. http://dx.doi.org/10.1049/iet-gtd.2014.0228
R.Sanchéz-García, M. Fenelly, S. Norris, N. Wright, G. Niblo, J. Brodski, and J. Bialek, Hierarchical Spectral Clustering of Power Grids, IEEE Trans. Power Syst., Vol. 29, No. 5, 2014. http://dx.doi.org/10.1109/tpwrs.2014.2306756
Laaksonen, H., Need for New Islanding Detection Schemes and Prioritization with Generator Grid Code Requirements, (2016) International Review of Electrical Engineering (IREE), 11 (2), pp. 160-170. http://dx.doi.org/10.15866/iree.v11i2.8348
B. Bollobás, Modern Graph Theory. Springer Verlag, New York, p. 6, 1998 http://dx.doi.org/10.1007/978-1-4612-0619-4
R.G. Busacker and T.L. Saaty, Finite Graphs and Networks: An Introduction with Applications, McGraw-Hill Book Company, New York, p. 109, 1965 http://dx.doi.org/10.2307/2282946
F.R.K. Chung, Spectral Graph Theory, in Proc. Regional Conference Series in Mathematics, vol. 92, pp. 3-6, 1996. http://dx.doi.org/10.1090/cbms/092
B. Mohar, The Laplacian Spectrum of Graphs, in Proc. Sixth International Conference on Theory and Applications of Graphs, Michigan, 1988
C. Mayer, Matrix Analysis and Applied Linear Algebra, SIAM, pp. 673-674, 2000
M.E.J. Newman, Finding Community Structure in Networks Using the Eigenvectors of Matrices, Phys. Rev. E.74, 2006. http://dx.doi.org/10.1103/physreve.74.036104
Ng, A.Y., Jordan, M.I., Weiss, Y., On spectral clustering: analysis and an algorithm, Adv. Neural Inf. Process. Syst., 2002, 2, pp. 849–856
Lee, J.R., Gharan, S.O., Trevisan, L.: Multi-way spectral partitioning and higher-order Cheeger inequalities, 44th Symp. on Theory of Computing, 2012, pp. 1117–1130 http://dx.doi.org/10.1145/2213977.2214078
T. Güler and G. Gross, Generalized Line Outage Distribution Factors, IEEE Trans. Power Syst., Power Engineering Letters, vol. 22, no. 2, pp. 879–881, May 2007. http://dx.doi.org/10.1109/tpwrs.2006.888950
K.M. Hall, An r-dimensional Quadratic Placement Algorithm, Management Science, vol. 17, No. 3, pp. 219-229, Nov. 1970. http://dx.doi.org/10.1287/mnsc.17.3.219
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spelling Moreno-Chuquen, Ricardof36efacf1d947d7410ab7d332d414753Obando Ceron, Johan Samirb8aaef71edc965de027f0670491e3948Universidad Autónoma de Occidente. Calle 25 115-85. Km 2 vía Cali-Jamundí2019-11-05T15:24:09Z2019-11-05T15:24:09Z201818276660http://hdl.handle.net/10614/11393https://doi.org/10.15866/iree.v13i3.14210The identification of topological vulnerabilities is a prerequisite for the study of security analysis. This paper presents a graph-theoretic framework to detect the minimum set of transmission lines interconnecting subnetworks inside of a power network. Moreover, the framework is used to develop a method to classify the criticality of substations. The approach can be used with power transfer distribution factors information to gain an insight about the power system security. Sometimes the power network exhibits high vulnerability related to critical transmission lines interconnecting critical substations from a physical point of view. The quantification of structural properties can provide meaningful information needed to assess and enhance the reliability and security of power system networks. The capabilities for the topological approach are illustrated on two large-scale networks. The proposed approach provides an effective tool for both real-time and offline environments for security analysis and controlapplication/pdfengInternational Review of Electrical Engineering, IREEDerechos Reservados - Universidad Autónoma de Occidentehttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_16ecNetwork topological notions for power systems security assessmentArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTREFinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Análisis de redes eléctricasElectric network analysisSistemas de interconexión eléctricaInterconnected electric utility systemsGraph theoryNetwork assessmentContingency analysisPower system security313Moreno-Chuquen, R., & Obando-Ceron, J. (2018). Network Topological Notions for Power Systems Security Assessment. International Review of Electrical Engineering (IREE), 237International Review of Electrical EngineeringA. J. Wood and B. F. Wollenberg, Power Generation, Operation, and Control, 3nd ed. New York, NY, USA: Wiley, 2014. http://dx.doi.org/10.1016/0140-6701(96)88715-7Rami Reddy, B., Sujatha, P., Siva Reddy, Y., Interline Power Flow Controller (IPFC) to Improve the Voltage Stability and Contingency Analysis in Power System, (2016) International Review of Electrical Engineering (IREE), 11 (1), pp. 109-115. http://dx.doi.org/10.15866/iree.v11i1.6790R. Albert, I. Albert, and G. L. Nakarado, Structural vulnerability of the North American power grid, Phys. Rev. E, vol. 69, pp. 1–10, Feb. 2004. http://dx.doi.org/10.1103/physreve.69.025103S. Arianos, E. Bompard, A. Carbone, and F. Xue, Power grid vulnerability: A complex network approach, Chaos, vol. 19, no. 01199, 2009. http://dx.doi.org/10.1063/1.3077229Y. Zhu, J. Yan, Y. Sun, and H. He, Revealing cascading failure vulnerability in power grids using risk-graph, IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 12, pp. 3274–3284, Dec. 2014. http://dx.doi.org/10.1109/tpds.2013.2295814P. Crucitti, V. Latora, and M. Marchiori, Locating critical lines in high-voltage electrical power grids, Fluctuation Noise Lett., vol. 5, no. 2, 2005. http://dx.doi.org/10.1142/s0219477505002562V. Latora and M. Marchiori, Vulnerability and protection of infrastructure networks, Phys. Rev. E, vol. 71, no. 015103(R), 2005. http://dx.doi.org/10.1103/physreve.71.015103 E. Bompard, D. Wu, F. Xue, Structural vulnerability of power systems: A topological approach, Electr. Power Syst. Res., vol. 81, pp. 1334–1340, 2011. http://dx.doi.org/10.1016/j.epsr.2011.01.021A. Peiravi, R. Ildarabadi, Graph partitioning Applications in Electrical Engineering with an Emphasis on Power System Intentional Islanding, (2009) International Review of Electrical Engineering (IREE), 4 (5), pp. 914-924T. Jiang, L. Bai, H. Jia, and F. Li, Spectral clustering-based partitioning of volt/VAR control areas in bulk power systems, IET Gener. Transm. Distrib. Vol. 11 Iss. 5, pp. 1126-1133, 2017. http://dx.doi.org/10.1049/iet-gtd.2016.0709J. Quirós-Tortós, R. Sanchéz-García, J. Brodski, J.Bialek, and V. Terzija, Constrained spectral clustering-based methodology for intentional controlled islanding of large-scale power systems, IET Gener. Transm. Distrib. Vol. 9 Iss. 1, pp. 31-42, 2014. http://dx.doi.org/10.1049/iet-gtd.2014.0228R.Sanchéz-García, M. Fenelly, S. Norris, N. Wright, G. Niblo, J. Brodski, and J. Bialek, Hierarchical Spectral Clustering of Power Grids, IEEE Trans. Power Syst., Vol. 29, No. 5, 2014. http://dx.doi.org/10.1109/tpwrs.2014.2306756Laaksonen, H., Need for New Islanding Detection Schemes and Prioritization with Generator Grid Code Requirements, (2016) International Review of Electrical Engineering (IREE), 11 (2), pp. 160-170. http://dx.doi.org/10.15866/iree.v11i2.8348B. Bollobás, Modern Graph Theory. Springer Verlag, New York, p. 6, 1998 http://dx.doi.org/10.1007/978-1-4612-0619-4R.G. Busacker and T.L. Saaty, Finite Graphs and Networks: An Introduction with Applications, McGraw-Hill Book Company, New York, p. 109, 1965 http://dx.doi.org/10.2307/2282946F.R.K. Chung, Spectral Graph Theory, in Proc. Regional Conference Series in Mathematics, vol. 92, pp. 3-6, 1996. http://dx.doi.org/10.1090/cbms/092B. Mohar, The Laplacian Spectrum of Graphs, in Proc. Sixth International Conference on Theory and Applications of Graphs, Michigan, 1988C. Mayer, Matrix Analysis and Applied Linear Algebra, SIAM, pp. 673-674, 2000M.E.J. Newman, Finding Community Structure in Networks Using the Eigenvectors of Matrices, Phys. Rev. E.74, 2006. http://dx.doi.org/10.1103/physreve.74.036104Ng, A.Y., Jordan, M.I., Weiss, Y., On spectral clustering: analysis and an algorithm, Adv. Neural Inf. Process. Syst., 2002, 2, pp. 849–856Lee, J.R., Gharan, S.O., Trevisan, L.: Multi-way spectral partitioning and higher-order Cheeger inequalities, 44th Symp. on Theory of Computing, 2012, pp. 1117–1130 http://dx.doi.org/10.1145/2213977.2214078T. Güler and G. Gross, Generalized Line Outage Distribution Factors, IEEE Trans. Power Syst., Power Engineering Letters, vol. 22, no. 2, pp. 879–881, May 2007. http://dx.doi.org/10.1109/tpwrs.2006.888950K.M. Hall, An r-dimensional Quadratic Placement Algorithm, Management Science, vol. 17, No. 3, pp. 219-229, Nov. 1970. http://dx.doi.org/10.1287/mnsc.17.3.219PublicationCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://dspace7-uao.metacatalogo.com/bitstreams/90909040-6ebd-403d-b7d6-d80639da190b/download4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81665https://dspace7-uao.metacatalogo.com/bitstreams/d18f5236-5d4f-417b-a5b2-7bbefd0edefa/download20b5ba22b1117f71589c7318baa2c560MD5310614/11393oai:dspace7-uao.metacatalogo.com:10614/113932024-01-19 16:27:00.126https://creativecommons.org/licenses/by-nc-nd/4.0/Derechos Reservados - Universidad Autónoma de Occidentemetadata.onlyhttps://dspace7-uao.metacatalogo.comRepositorio UAOrepositorio@uao.edu.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