Implications of the Dichotomy of Modal Participation Factors for Monitoring and Control of Electric Power Networks

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dc.contributor.advisorAbed, Eyaden_US
dc.contributor.advisorJacob, Bruceen_US
dc.contributor.authorTschirhart, Paul Kentonen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2014-02-06T06:32:29Z
dc.date.available2014-02-06T06:32:29Z
dc.date.issued2013en_US
dc.description.abstractSteadily increasing demand for electricity has led to today's electric power networks often being stressed to their stability limits. Improved methods of stability monitoring and control placement are needed to manage the increased stress on power networks. Modal participation factors have been used for several decades in the analysis of modal behavior in power networks. Recently a dichotomy was discovered in modal participation, indicating that the participation of system states in system modes should be calculated differently from the participation of system modes in system states. This masters thesis numerically explores possible roles for these new participation factor definitions in power network monitoring and control. The results suggest that the mode in state participation factors are best employed in modal monitoring (especially in deciding which variables to monitor to best detect specific modes), while the state in mode participation factors are best suited to control applications (such as controller placement).en_US
dc.identifier.urihttp://hdl.handle.net/1903/14855
dc.language.isoenen_US
dc.subject.pqcontrolledElectrical engineeringen_US
dc.subject.pquncontrolledModal Analysisen_US
dc.subject.pquncontrolledParticipation Factoren_US
dc.subject.pquncontrolledPower Networken_US
dc.subject.pquncontrolledPower Systemen_US
dc.subject.pquncontrolledProny Analysisen_US
dc.titleImplications of the Dichotomy of Modal Participation Factors for Monitoring and Control of Electric Power Networksen_US
dc.typeThesisen_US

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