dc.creator | Zang, Tianlei | es |
dc.creator | Lei, Jieyu | es |
dc.creator | Wei, Xiaoguang | es |
dc.creator | Huang, Tao | es |
dc.creator | Wang, Tao | es |
dc.creator | Pérez Jiménez, Mario de Jesús | es |
dc.creator | Lin, Hua | es |
dc.date.accessioned | 2020-04-07T08:55:20Z | |
dc.date.available | 2020-04-07T08:55:20Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Zang, 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.issn | 2169-3536 | es |
dc.identifier.uri | https://hdl.handle.net/11441/94954 | |
dc.description.abstract | Security 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.sponsorship | National Natural Science Foundation of China under Grant U1734202 | es |
dc.description.sponsorship | National Key Research and Development Plan of China under Grant 2017YFB1200802-12 | es |
dc.description.sponsorship | National Natural Science Foundation of China under Grant 51877181 | es |
dc.description.sponsorship | National Natural Science Foundation of China under Grant 61703345 | es |
dc.description.sponsorship | Chinese Academy of Sciences, under Grant 2018-2019-01 | es |
dc.format | application/pdf | es |
dc.format.extent | 10 | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | IEEE Access, 7, 88927-88936. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Vulnerability | es |
dc.subject | Complex network theory | es |
dc.subject | Adjacent graph | es |
dc.subject | Branch importance index | es |
dc.title | Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.projectID | U1734202 | es |
dc.relation.projectID | 2017YFB1200802-12 | es |
dc.relation.projectID | 51877181 | es |
dc.relation.projectID | 61703345 | es |
dc.relation.projectID | 2018-2019-01 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8752207 | es |
dc.identifier.doi | 10.1109/ACCESS.2019.2926148 | es |
dc.contributor.group | Universidad de Sevilla. TIC193: Computación Natural | es |
dc.journaltitle | IEEE Access | es |
dc.publication.volumen | 7 | es |
dc.publication.initialPage | 88927 | es |
dc.publication.endPage | 88936 | es |
dc.contributor.funder | National Natural Science Foundation of China | es |
dc.contributor.funder | Chinese Academy of Sciences | es |