Planning and optimization of nuclear-renewable micro hybrid energy systems for off-grid applications

dc.contributor.advisorGaber, Hossam
dc.contributor.authorAbdussami, Md Rafiul
dc.date.accessioned2021-02-26T14:50:22Z
dc.date.accessioned2022-03-25T18:49:42Z
dc.date.available2021-02-26T14:50:22Z
dc.date.available2022-03-25T18:49:42Z
dc.date.issued2020-11-01
dc.degree.disciplineNuclear Engineering
dc.degree.levelMaster of Applied Science (MASc)
dc.description.abstractResilient operation of medium/large scale off-grid energy systems is a key challenge for energy crisis solutions, which requires continuous and sustainable energy resources. In this context, microreactors are incorporated with renewables to provide a continuous, reliable, and sustainable energy supply. The research is apportioned into two parts. In the first part, the study proposes three methods of hybridization for planning and identifying the most efficient Nuclear-Renewable Micro Hybrid Energy System (N-R MHES). Based on proposed hybridization techniques, mathematical modeling of N-R MHES's economy is carried out. An artificial intelligence optimization technique is used to achieve the optimal system configurations of different N-R MHESs and determine the best hybridized nuclear-renewable system. In the second portion of the study, a traditional technology, diesel-fired Micro Energy Grid (MEG), is compared with the best configured N-R MHES. This study of the comparison indicates that microreactor-based MEGs could be a potential replacement for diesel-fired MEGs.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.identifier.urihttps://hdl.handle.net/10155/1243
dc.language.isoenen
dc.subjectNuclear poweren
dc.subjectRenewable energyen
dc.subjectHybrid energy systemen
dc.subjectEnergy managementen
dc.subjectSensitivity assessmenten
dc.titlePlanning and optimization of nuclear-renewable micro hybrid energy systems for off-grid applicationsen
dc.typeThesisen
thesis.degree.disciplineNuclear Engineering
thesis.degree.grantorUniversity of Ontario Institute of Technology
thesis.degree.nameMaster of Applied Science (MASc)

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