Methodology for a Security-Dependability Adaptive Protection Scheme based on Data Mining

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dc.contributor.authorBernabeu, Emanuelen
dc.contributor.committeecochairThorp, James S.en
dc.contributor.committeecochairCenteno, Virgilio A.en
dc.contributor.committeememberDe La Ree, Jaimeen
dc.contributor.committeememberDaSilva, Luiz A.en
dc.contributor.committeememberKohler, Werner E.en
dc.contributor.committeememberLiu, Yiluen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2014-03-14T20:20:48Zen
dc.date.adate2010-01-21en
dc.date.available2014-03-14T20:20:48Zen
dc.date.issued2009-12-09en
dc.date.rdate2010-01-21en
dc.date.sdate2009-12-17en
dc.description.abstractThe power industry is currently in the process of re-inventing itself. The unbundling of the traditional monopolistic structure that gave birth to a deregulated electricity market, the mass tendency towards a greener use of energy, the new emphasis on distributed generation and alternative renewable resources, and new emerging technologies have revolutionized the century old industry. Recent blackouts offer testimonies of the crucial role played by protection relays in a reliable power system. It is argued that embracing the paradigm shift of adaptive protection is a fundamental step towards a reliable power grid. The adaptive philosophy of protection systems acknowledges that relays may change their characteristics in order to tailor their operation to prevailing system conditions. The purpose of this dissertation is to present methodology to implement a security/dependability adaptive protection scheme. It is argued that the likelihood of hidden failures and potential cascading events can be significantly reduced by adjusting the security/dependability balance of protection systems to better suit prevailing system conditions. The proposed methodology is based on Wide Area Measurements (WAMs) obtained with the aid of Phasor Measurement Units (PMUs). A Data Mining algorithm known as Decision Trees is used to classify the power system state and to predict the optimal security/dependability bias of a critical protection scheme.en
dc.description.degreePh. D.en
dc.identifier.otheretd-12172009-201325en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12172009-201325/en
dc.identifier.urihttp://hdl.handle.net/10919/30131en
dc.publisherVirginia Techen
dc.relation.haspartBernabeu_EE_D_2009.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectwide area measurementsen
dc.subjectdata miningen
dc.subjectdecision treesen
dc.subjectadaptive protectionen
dc.subjectcritical locationsen
dc.titleMethodology for a Security-Dependability Adaptive Protection Scheme based on Data Miningen
dc.typeDissertationen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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