Identifying multiple interacting bad data in power system state estimation

dc.contributorUniversidade Estadual de Campinas (UNICAMP)
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:21:39Z
dc.date.accessioned2022-10-05T17:58:08Z
dc.date.available2014-05-27T11:21:39Z
dc.date.available2022-10-05T17:58:08Z
dc.date.created2014-05-27T11:21:39Z
dc.date.issued2005-10-31
dc.identifier2005 IEEE Power Engineering Society General Meeting, v. 1, p. 571-577.
dc.identifierhttp://hdl.handle.net/11449/68458
dc.identifier10.1109/PES.2005.1489754
dc.identifier2-s2.0-27144505813
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3917996
dc.description.abstractThis paper presents an intelligent search strategy for the conforming bad data errors identification in the generalized power system state estimation, by using the tabu search meta heuristic. The main objective is to detect critical errors involving both analog and topology errors. These errors are represented by conforming errors, whose nature affects measurements that actually do not present bad data and also the conventional bad data identification strategies based on the normalized residual methods. ©2005 IEEE.
dc.languageeng
dc.relation2005 IEEE Power Engineering Society General Meeting
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectData reduction
dc.subjectErrors
dc.subjectHeuristic methods
dc.subjectIdentification (control systems)
dc.subjectStrategic planning
dc.subjectTopology
dc.subjectData errors
dc.subjectMeta heuristics
dc.subjectPower system
dc.subjectTopology errors
dc.subjectElectric power systems
dc.titleIdentifying multiple interacting bad data in power system state estimation
dc.typeTrabalho apresentado em evento


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