PMU-Based Applications for Improved Monitoring and Protection of Power Systems

dc.contributor.authorPal, Anamitraen
dc.contributor.committeechairThorp, James S.en
dc.contributor.committeememberShukla, Sandeep K.en
dc.contributor.committeememberCenteno, Virgilio A.en
dc.contributor.committeememberPhadke, Arun G.en
dc.contributor.committeememberTaaffe, Michael R.en
dc.contributor.committeememberDe La Ree, Jaimeen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2014-12-09T16:36:35Zen
dc.date.available2014-12-09T16:36:35Zen
dc.date.issued2014-05-07en
dc.description.abstractMonitoring and protection of power systems is a task that has manifold objectives. Amongst others, it involves performing data mining, optimizing available resources, assessing system stresses, and doing data conditioning. The role of PMUs in fulfilling these four objectives forms the basis of this dissertation. Classification and regression tree (CART) built using phasor data has been extensively used in power systems. The splits in CART are based on a single attribute or a combination of variables chosen by CART itself rather than the user. But as PMU data consists of complex numbers, both the attributes, should be considered simultaneously for making critical decisions. An algorithm is proposed here that expresses high dimensional, multivariate data as a single attribute in order to successfully perform splits in CART. In order to reap maximum benefits from placement of PMUs in the power grid, their locations must be selected judiciously. A gradual PMU placement scheme is developed here that ensures observability as well as protects critical parts of the system. In order to circumvent the computational burden of the optimization, this scheme is combined with a topology-based system partitioning technique to make it applicable to virtually any sized system. A power system is a dynamic being, and its health needs to be monitored at all times. Two metrics are proposed here to monitor stress of a power system in real-time. Angle difference between buses located across the network and voltage sensitivity of buses lying in the middle are found to accurately reflect the static and dynamic stress of the system. The results indicate that by setting appropriate alerts/alarm limits based on these two metrics, a more secure power system operation can be realized. A PMU-only linear state estimator is intrinsically superior to its predecessors with respect to performance and reliability. However, ensuring quality of the data stream that leaves this estimator is crucial. A methodology for performing synchrophasor data conditioning and validation that fits neatly into the existing linear state estimation formulation is developed here. The results indicate that the proposed methodology provides a computationally simple, elegant solution to the synchrophasor data quality problem.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:2746en
dc.identifier.urihttp://hdl.handle.net/10919/51093en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectBinary Integer Programmingen
dc.subjectData Conditioningen
dc.subjectFisher Linear Discriminant (FLD)en
dc.subjectKalman Filteren
dc.subjectObservabilityen
dc.subjectPhasor Measurement Units (PMUs)en
dc.subjectStress Assessmenten
dc.subjectWide Area Measurement Systems (WAMS)en
dc.titlePMU-Based Applications for Improved Monitoring and Protection of Power Systemsen
dc.typeDissertationen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en
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