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dc.contributor.advisorGrijalva, Santiago
dc.contributor.advisorEgerstedt, Magnus
dc.contributor.advisorAhmed, Shabbir
dc.contributor.advisorMeliopoulos, Sakis
dc.contributor.advisorFerri, Bonnie
dc.contributor.advisorSaeedifard, Maryam
dc.contributor.authorCostley, Mitcham Hudson
dc.date.accessioned2016-05-27T13:10:33Z
dc.date.available2016-05-27T13:10:33Z
dc.date.created2015-05
dc.date.issued2015-04-03
dc.date.submittedMay 2015
dc.identifier.urihttp://hdl.handle.net/1853/54890
dc.description.abstractThe contributions of this research are a scalable formulation and solution method for decentralized unit commitment, experimental results comparing decentralized unit commitment solution times to conventional unit commitment methods, a demonstration of the benefits of faster unit commitment computation time, and extensions of decentralized unit commitment to handle system network security constraints. We begin with a discussion motivating the shift from centralized power system control architectures to decentralized architectures and describe the characteristics of such an architecture. We then develop a formulation and solution method to solve decentralized unit commitment by adapting an existing approach for separable convex optimization problems to the nonconvex domain of unit commitment. The potential computational speed benefits of the novel decentralized unit commitment approach are then further investigated through a rolling-horizon framework that represents how system operators make decisions and adjustments online as new information is revealed. Finally, the decentralized unit commitment approach is extended to include network contingency constraints, a crucial function for the maintenance of system security. The results indicate decentralized unit commitment holds promise as a way of coordinating system operations in a future decentralized grid and also may provide a way to leverage parallel computing resources to solve large-scale unit commitment problems with greater speed and model fidelity than is possible with conventional methods.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectPower systems
dc.subjectUnit commitment
dc.subjectOptimization
dc.titleProsumer-based decentralized unit commitment for future electricity grids
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentElectrical and Computer Engineering
thesis.degree.levelDoctoral
dc.date.updated2016-05-27T13:10:33Z


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