Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation

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dc.contributor.authorZhao, Junboen
dc.contributor.authorNetto, Marcosen
dc.contributor.authorHuang, Zhenyuen
dc.contributor.authorYu, Samson Shenglongen
dc.contributor.authorGomez-Exposito, Antonioen
dc.contributor.authorWang, Shaobuen
dc.contributor.authorKamwa, Innocenten
dc.contributor.authorAkhlaghi, Shahrokhen
dc.contributor.authorMili, Lamine M.en
dc.contributor.authorTerzija, Vladimiren
dc.contributor.authorMeliopoulos, A. P. Sakisen
dc.contributor.authorPal, Bikashen
dc.contributor.authorSingh, Abhinav Kumaren
dc.contributor.authorAbur, Alien
dc.contributor.authorBi, Tianshuen
dc.contributor.authorRouhani, Alirezaen
dc.date.accessioned2024-01-23T18:17:37Zen
dc.date.available2024-01-23T18:17:37Zen
dc.date.issued2020-09-30en
dc.description.abstractPower system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today's synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems and novel system monitoring, control and protection tools to achieve better reliability and resiliency.en
dc.description.versionPublished versionen
dc.format.extentPages 2462-2472en
dc.format.extent11 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1109/TPWRS.2020.3028047en
dc.identifier.eissn1558-0679en
dc.identifier.issn0885-8950en
dc.identifier.issue3en
dc.identifier.orcidMili, Lamine [0000-0001-6134-3945]en
dc.identifier.urihttps://hdl.handle.net/10919/117618en
dc.identifier.volume36en
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000641975800069&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsPublic Domain (U.S.)en
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/en
dc.subjectElectronic mailen
dc.subjectObservabilityen
dc.subjectPower system dynamicsen
dc.subjectState estimationen
dc.subjectKalman filtersen
dc.subjectPhasor measurement unitsen
dc.subjectEnergy managementen
dc.subjectDynamic state estimationen
dc.subjectkalman filteringen
dc.subjectconverter interfaced generationen
dc.subjectlow inertiaen
dc.subjectmonitoringen
dc.subjectparameter estimationen
dc.subjectpower system stabilityen
dc.subjectstatic state estimationen
dc.subjectsynchronous machinesen
dc.subjectsynchrophasor measurementsen
dc.titleRoles of Dynamic State Estimation in Power System Modeling, Monitoring and Operationen
dc.title.serialIEEE Transactions on Power Systemsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dc.type.otherJournalen
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

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