Probabilistic Load-Margin Assessment using Vine Copula and Gaussian Process Emulation

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dc.contributor.authorXu, Yijunen
dc.contributor.authorKarra, Kiranen
dc.contributor.authorMili, Lamine M.en
dc.contributor.authorKorkali, Merten
dc.contributor.authorChen, Xiaoen
dc.contributor.authorHu, Zhixiongen
dc.date.accessioned2024-01-22T15:43:01Zen
dc.date.available2024-01-22T15:43:01Zen
dc.date.issued2020en
dc.description.abstractThe increasing penetration of renewable energy along with the variations of the loads bring large uncertainties in the power system states that are threatening the security of power system planning and operation. Facing these challenges, this paper proposes a cost-effective, nonparametric method to quantity the impact of uncertain power injections on the load margins. First, we propose to generate system uncertain inputs via a novel vine copula due to its capability in simulating complex multivariate highly dependent model inputs. Furthermore, to reduce the prohibitive computational time required in the traditional Monte-Carlo method, we propose to use a nonparametric, Gaussian-process-emulator-based reduced-order model to replace the original complicated continuation power-flow model. This emulator allows us to execute the time-consuming continuation power-flow solver at the sampled values with a negligible computational cost. The simulations conducted on the IEEE 57-bus system, to which correlated renewable generation are attached, reveal the excellent performance of the proposed method.en
dc.description.versionPublished versionen
dc.format.extent5 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1109/PESGM41954.2020.9281551en
dc.identifier.eissn1944-9933en
dc.identifier.isbn9781728155081en
dc.identifier.issn1944-9925en
dc.identifier.orcidMili, Lamine [0000-0001-6134-3945]en
dc.identifier.urihttps://hdl.handle.net/10919/117518en
dc.identifier.volume2020-Augusten
dc.language.isoenen
dc.publisherIEEEen
dc.rightsPublic Domain (U.S.)en
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/en
dc.subjectProbabilistic load marginen
dc.subjectGaussian process emulatoren
dc.subjectvine copulaen
dc.subjectuncertaintyen
dc.subjectvoltage stabilityen
dc.titleProbabilistic Load-Margin Assessment using Vine Copula and Gaussian Process Emulationen
dc.title.serial2020 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM)en
dc.typeConference proceedingen
dc.type.dcmitypeTexten
dc.type.otherProceedings Paperen
dc.type.otherBook in seriesen
pubs.finish-date2020-08-06en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Electrical and Computer Engineeringen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen
pubs.start-date2020-08-03en

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