A Derivative-Free Observability Analysis Method of Stochastic Power Systems

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dc.contributor.authorZheng, Zongshengen
dc.contributor.authorXu, Yijunen
dc.contributor.authorMili, Lamine M.en
dc.contributor.authorLiu, Zhigangen
dc.contributor.authorKorkali, Merten
dc.contributor.authorWang, Yuhongen
dc.date.accessioned2024-01-22T20:35:06Zen
dc.date.available2024-01-22T20:35:06Zen
dc.date.issued2021en
dc.description.abstractThe observability analysis of a time-varying nonlinear dynamic model has recently attracted the attention of power engineers due to its vital role in power system dynamic state estimation. Generally speaking, due to the nonlinearity of the power system dynamic model, the traditional derivative-based observability analysis approaches either rely on the linear approximation to simplify the problem or require a complicated derivation procedure that ignores the uncertainties of the dynamic system model and of the observations represented by stochastic noises. Facing this challenge, we propose a novel polynomial-chaos-based derivative-free observability analysis approach that not only brings a low complexity, but also enables us to quantify the degree of observability by considering the stochastic nature of the dynamic systems. The excellent performances of the proposed method is demonstrated using simulations of a decentralized dynamic state estimation performed on a power system using a synchronous generator model with IEEE-DC1A exciter and a TGOV1 turbine-governor.en
dc.description.versionPublished versionen
dc.format.extent5 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1109/PESGM46819.2021.9637959en
dc.identifier.eissn1944-9933en
dc.identifier.isbn9781665405072en
dc.identifier.issn1944-9925en
dc.identifier.orcidMili, Lamine [0000-0001-6134-3945]en
dc.identifier.urihttps://hdl.handle.net/10919/117586en
dc.identifier.volume2021-Julyen
dc.language.isoenen
dc.publisherIEEEen
dc.rightsPublic Domain (U.S.)en
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/en
dc.subjectDynamic state estimationen
dc.subjectobservability analysisen
dc.subjectderivative-free analysisen
dc.subjectpolynomial chaosen
dc.titleA Derivative-Free Observability Analysis Method of Stochastic Power Systemsen
dc.title.serial2021 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-date2021-07-29en
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-date2021-07-26en

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