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dc.contributor.authorNetto, Marcosen_US
dc.date.accessioned2019-02-20T09:00:18Z
dc.date.available2019-02-20T09:00:18Z
dc.date.issued2019-02-19
dc.identifier.othervt_gsexam:18647en_US
dc.identifier.urihttp://hdl.handle.net/10919/87728
dc.description.abstractThe study of nonlinear dynamical systems via the spectrum of the Koopman operator has emerged as a paradigm shift, from the Poincaré's geometric picture that centers the attention on the evolution of states, to the Koopman operator's picture that focuses on the evolution of observables. The Koopman operator-theoretic framework rests on the idea of lifting the states of a nonlinear dynamical system to a higher dimensional space; these lifted states are referred to as the Koopman eigenfunctions. To determine the Koopman eigenfunctions, one performs a nonlinear transformation of the states by relying on the so-called observables, that is, scalar-valued functions of the states. In other words, one executes a change of coordinates from the state space to another set of coordinates, which are denominated Koopman canonical coordinates. The variables defined on these intrinsic coordinates will evolve linearly in time, despite the underlying system being nonlinear. Since the Koopman operator is linear, it is natural to exploit its spectral properties. In fact, the theory surrounding the spectral properties of linear operators has well-known implications in electric power systems. Examples include small-signal stability analysis and direct methods for transient stability analysis based on the Lyapunov function. From the applications' standpoint, this framework based on the Koopman operator is attractive because it is capable of revealing linear and nonlinear modes by only applying well-established tools that have been developed for linear systems. With the challenges associated with the high-dimensionality and increasing uncertainties in the power systems models, researchers and practitioners are seeking alternative modeling approaches capable of incorporating information from measurements. This is fueled by an increasing amount of data made available by the wide-scale deployment of measuring devices such as phasor measurement units and smart meters. Along these lines, the Koopman operator theory is a promising framework for the integration of data analysis into our mathematical knowledge and is bringing an exciting perspective to the community. The present dissertation reports on the application of the Koopman operator for identification, estimation, and control of electric power systems. A dynamic state estimator based on the Koopman operator has been developed and compares favorably against model-based approaches, in particular for centralized dynamic state estimation. Also, a data-driven method to compute participation factors for nonlinear systems based on Koopman mode decomposition has been developed; it generalizes the original definition of participation factors under certain conditions.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis item is protected by copyright and/or related rights. Some uses of this item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectDynamical systemsen_US
dc.subjectKalman filteringen_US
dc.subjectKoopman operatoren_US
dc.subjectKoopman mode decompositionen_US
dc.subjectmodal analysisen_US
dc.subjectnonlinear identificationen_US
dc.subjectnonlinear dynamicsen_US
dc.subjectparticipation factorsen_US
dc.subjectrobust estimation and filteringen_US
dc.subjectpower system stability and controlen_US
dc.titleRobust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Frameworken_US
dc.typeDissertationen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.description.degreePHDen_US
thesis.degree.namePHDen_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineElectrical Engineeringen_US
dc.contributor.committeechairMili, Lamine Men_US
dc.contributor.committeemembervon Spakovsky, Michael Ren_US
dc.contributor.committeememberStilwell, Daniel Jen_US
dc.contributor.committeememberSusuki, Yoshihikoen_US
dc.contributor.committeememberKekatos, Vasileiosen_US
dc.contributor.committeememberCenteno, Virgilio Aen_US


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