Power System Coherency Identification Using Nonlinear Koopman Mode Analysis
| dc.contributor.author | Tbaileh, Ahmad Anan | en |
| dc.contributor.committeechair | Mili, Lamine M. | en |
| dc.contributor.committeemember | Baumann, William T. | en |
| dc.contributor.committeemember | Evrenosoglu, Cansin Yaman | en |
| dc.contributor.department | Electrical and Computer Engineering | en |
| dc.date.accessioned | 2014-07-02T08:00:52Z | en |
| dc.date.available | 2014-07-02T08:00:52Z | en |
| dc.date.issued | 2014-07-01 | en |
| dc.description.abstract | In this thesis, we apply nonlinear Koopman mode analysis to decompose the swing dynamics of a power system into modes of oscillation, which are identified by analyzing the Koopman operator, a linear infinite-dimensional operator that may be defined for any nonlinear dynamical system. Specifically, power system modes of oscillation are identified through spectral analysis of the Koopman operator associated with a particular observable. This means that they can be determined directly from measurements. These modes, referred to as Koopman modes, are single-frequency oscillations, which may be extracted from nonlinear swing dynamics under small and large disturbances. They have an associated temporal frequency and growth rate. Consequently, they may be viewed as a nonlinear generalization of eigen-modes of a linearized system. Koopman mode analysis has been also applied to identify coherent swings and coherent groups of machines of a power system. This will allow us to carry out a model reduction of a large-scale system and to derive a precursor to monitor the loss of transient stability. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:3055 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/49261 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | power system stability | en |
| dc.subject | coherency identification | en |
| dc.subject | modal analysis | en |
| dc.subject | model reduction | en |
| dc.title | Power System Coherency Identification Using Nonlinear Koopman Mode Analysis | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Electrical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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