Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/11464
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dc.contributor.authorVaccaro, A-
dc.contributor.authorPisani, C-
dc.contributor.authorZobaa, AF-
dc.date.accessioned2015-10-12T09:22:12Z-
dc.date.available2015-01-01-
dc.date.available2015-10-12T09:22:12Z-
dc.date.issued2015-
dc.identifier.citationIET Generation, Transmission and Distribution, 9(13): 1544 - 1552, (2015)en_US
dc.identifier.issn1751-8687-
dc.identifier.urihttp://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2015.0197-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/11464-
dc.description.abstractIn this study, the role of self-validated computing for solving the energy hub-scheduling problem in the presence of multiple and heterogeneous sources of data uncertainties is explored and a new solution paradigm based on affine arithmetic is conceptualised. The benefits deriving from the application of this methodology are analysed in details, and several numerical results are presented and discussed.en_US
dc.format.extent1544 - 1552-
dc.language.isoenen_US
dc.publisherIETen_US
dc.subjectPower system interconnectionen_US
dc.subjectAffine transformsen_US
dc.subjectPower generation schedulingen_US
dc.titleAffine arithmetic-based methodology for energy hub operation-scheduling in the presence of data uncertaintyen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1049/iet-gtd.2015.0197-
dc.relation.isPartOfIET Generation, Transmission and Distribution-
pubs.issue13-
pubs.publication-statusPublished-
pubs.publication-statusPublished-
pubs.volume9-
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

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