Mostrar el registro sencillo del ítem

Artículo

dc.creatorZang, Tianleies
dc.creatorLei, Jieyues
dc.creatorWei, Xiaoguanges
dc.creatorHuang, Taoes
dc.creatorWang, Taoes
dc.creatorPérez Jiménez, Mario de Jesúses
dc.creatorLin, Huaes
dc.date.accessioned2020-04-07T08:55:20Z
dc.date.available2020-04-07T08:55:20Z
dc.date.issued2019
dc.identifier.citationZang, T., Lei, J., Wei, X., Huang, T., Wang, T., Pérez Jiménez, M.d.J. y Lin, H. (2019). Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches. IEEE Access, 7, 88927-88936.
dc.identifier.issn2169-3536es
dc.identifier.urihttps://hdl.handle.net/11441/94954
dc.description.abstractSecurity issues related to vulnerability assessment in electrical networks are necessary for operators to identify the critical branches. At present, using complex network theory to assess the structural vulnerability of the electrical network is a popular method. However, the complex network theory cannot be comprehensively applicable to the operational vulnerability assessment of the electrical network because the network operation is closely dependent on the physical rules not only on the topological structure. To overcome the problem, an adjacent graph (AG) considering the topological, physical, and operational features of the electrical network is constructed to replace the original network. Through the AG, a branch importance index that considers both the importance of a branch and the fault adjacent relationships among branches is constructed to evaluate the electrical network vulnerability. The IEEE 118-bus system and the French grid are employed to validate the effectiveness of the proposed method.es
dc.description.sponsorshipNational Natural Science Foundation of China under Grant U1734202es
dc.description.sponsorshipNational Key Research and Development Plan of China under Grant 2017YFB1200802-12es
dc.description.sponsorshipNational Natural Science Foundation of China under Grant 51877181es
dc.description.sponsorshipNational Natural Science Foundation of China under Grant 61703345es
dc.description.sponsorshipChinese Academy of Sciences, under Grant 2018-2019-01es
dc.formatapplication/pdfes
dc.format.extent10es
dc.language.isoenges
dc.publisherIEEE Computer Societyes
dc.relation.ispartofIEEE Access, 7, 88927-88936.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectVulnerabilityes
dc.subjectComplex network theoryes
dc.subjectAdjacent graphes
dc.subjectBranch importance indexes
dc.titleAdjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Brancheses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificiales
dc.relation.projectIDU1734202es
dc.relation.projectID2017YFB1200802-12es
dc.relation.projectID51877181es
dc.relation.projectID61703345es
dc.relation.projectID2018-2019-01es
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8752207es
dc.identifier.doi10.1109/ACCESS.2019.2926148es
dc.contributor.groupUniversidad de Sevilla. TIC193: Computación Naturales
dc.journaltitleIEEE Accesses
dc.publication.volumen7es
dc.publication.initialPage88927es
dc.publication.endPage88936es
dc.contributor.funderNational Natural Science Foundation of Chinaes
dc.contributor.funderChinese Academy of Scienceses

FicherosTamañoFormatoVerDescripción
08752207.pdf17.78MbIcon   [PDF] Ver/Abrir  

Este registro aparece en las siguientes colecciones

Mostrar el registro sencillo del ítem

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Excepto si se señala otra cosa, la licencia del ítem se describe como: Attribution-NonCommercial-NoDerivatives 4.0 Internacional