Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77399
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dc.contributorDepartment of Electronic and Information Engineeringen_US
dc.creatorGanganath, Nen_US
dc.creatorWang, Jen_US
dc.creatorXu, Xen_US
dc.creatorCheng, CTen_US
dc.creatorTse, CKen_US
dc.date.accessioned2018-08-20T09:56:14Z-
dc.date.available2018-08-20T09:56:14Z-
dc.identifier.issn1551-3203en_US
dc.identifier.urihttp://hdl.handle.net/10397/77399-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.en_US
dc.rightsThe following publication Ganganath, N., Wang, J. V., Xu, X., Cheng, C. T., & Chi, K. T. (2017). Agglomerative Clustering Based Network Partitioning for Parallel Power System Restoration. IEEE Transactions on Industrial Informatics, 14 (8), 3325-3333 is available at https://doi.org/10.1109/TII.2017.2780167.en_US
dc.subjectAgglomerative clusteringen_US
dc.subjectClustering algorithmsen_US
dc.subjectGeneratorsen_US
dc.subjectInformaticsen_US
dc.subjectNetwork partitioningen_US
dc.subjectParallel restorationen_US
dc.subjectPartitioning algorithmsen_US
dc.subjectPower system restorationen_US
dc.subjectPower system stabilityen_US
dc.subjectPower systemsen_US
dc.subjectSectionalisingen_US
dc.subjectSmart griden_US
dc.titleAgglomerative clustering based network partitioning for parallel power system restorationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage3325en_US
dc.identifier.epage3333en_US
dc.identifier.volume14en_US
dc.identifier.issue8en_US
dc.identifier.doi10.1109/TII.2017.2780167en_US
dcterms.abstractIEEE After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of partitioning process. The second step ensures the satisfaction of modelled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39- and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike many existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution. The proposed strategy is implemented and evaluated on IEEE 39- and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on industrial informatics, 2017, v. 14, no. 8, p. 3325-3333en_US
dcterms.isPartOfIEEE transactions on industrial informaticsen_US
dcterms.issued2017-
dc.identifier.scopus2-s2.0-85038385242-
dc.identifier.eissn1941-0050en_US
dc.description.validate201808 bcmaen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera0251-n01, OA_IR/PIRA-
dc.description.pubStatusPublisheden_US
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