Electric power systems transient stability analysis by neural networks

dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:18:02Z
dc.date.available2014-05-27T11:18:02Z
dc.date.created2014-05-27T11:18:02Z
dc.date.issued1995-12-01
dc.identifierMidwest Symposium on Circuits and Systems, v. 2, p. 1305-1308.
dc.identifierhttp://hdl.handle.net/11449/64681
dc.identifier10.1109/MWSCAS.1995.510337
dc.identifierWOS:A1996BF75Z00323
dc.identifier2-s2.0-0029463113
dc.description.abstractThis work aims to investigate the use of artificial neural networks in the analysis of the transient stability of Electric Power Systems (determination of critical clearing time for short-circuit faults type with electric power transmission line outage), using a supervised feedforward neural network. To illustrate the proposed methodology, it is presented an application considering a system having by 08 synchronous machines, 23 transmission lines, and 17 buses.
dc.languageeng
dc.relationMidwest Symposium on Circuits and Systems
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectAdaptive algorithms
dc.subjectBackpropagation
dc.subjectComputational methods
dc.subjectComputer simulation
dc.subjectElectric power transmission
dc.subjectFeedforward neural networks
dc.subjectFunctions
dc.subjectIterative methods
dc.subjectShort circuit currents
dc.subjectSynchronous machinery
dc.subjectTransients
dc.subjectTransmission line theory
dc.subjectCritical clearing time
dc.subjectNeuron weight
dc.subjectQuadratic error gradient
dc.subjectShort circuit faults
dc.subjectTransient stability analysis
dc.subjectElectric power systems
dc.titleElectric power systems transient stability analysis by neural networks
dc.typeActas de congresos


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