{"id":{"repo_id":"uoit","oai_identifier":"oai:ontariotechu.scholaris.ca:10155/1243"},"canonical_url":"https://search.dev.ndltd.org/etd/uoit/oai:ontariotechu.scholaris.ca:10155/1243","repository":{"repo_id":"uoit","name":"Ontario Institute of Technology","base_url":"https://ontariotechu.scholaris.ca/server/oai/request"},"display":{"title":"Planning and optimization of nuclear-renewable micro hybrid energy systems for off-grid applications","abstract":"Resilient 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.","abstract_html":"Resilient 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.","abstract_has_math":false,"creators":["Abdussami, Md Rafiul"],"institution":"University of Ontario Institute of Technology","degree_name":"Master of Applied Science (MASc)","degree_level":null,"degree_discipline":"Nuclear Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Gaber, Hossam"],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-11-01","date_published":"2020-11-01","updated_at":"2026-07-24T05:35:39Z","subjects":["Nuclear power","Renewable energy","Hybrid energy system","Energy management","Sensitivity assessment"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10155/1243","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Gaber, Hossam"]},{"key":"dc:creator","label":"Author","values":["Abdussami, Md Rafiul"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-02-26T14:50:22Z","2022-03-25T18:49:42Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-02-26T14:50:22Z","2022-03-25T18:49:42Z"]},{"key":"dc:date.issued","label":"Date","values":["2020-11-01"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Nuclear Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Applied Science (MASc)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Ontario Institute of Technology"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Nuclear power","Renewable energy","Hybrid energy system","Energy management","Sensitivity assessment"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10155/1243"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Resilient 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."]},{"key":"dc:title","label":"Title","values":["Planning and optimization of nuclear-renewable micro hybrid energy systems for off-grid applications"]}]}],"canonical_facts":{"dc:contributor.advisor":["Gaber, Hossam"],"dc:creator":["Abdussami, Md Rafiul"],"dc:date.accessioned":["2021-02-26T14:50:22Z","2022-03-25T18:49:42Z"],"dc:date.available":["2021-02-26T14:50:22Z","2022-03-25T18:49:42Z"],"dc:date.issued":["2020-11-01"],"dc:description.abstract":["Resilient 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."],"dc:identifier.uri":["https://hdl.handle.net/10155/1243"],"dc:language.iso":["en"],"dc:subject":["Nuclear power","Renewable energy","Hybrid energy system","Energy management","Sensitivity assessment"],"dc:title":["Planning and optimization of nuclear-renewable micro hybrid energy systems for off-grid applications"],"dc:type":["Thesis"],"thesis:degree_discipline":["Nuclear Engineering"],"thesis:degree_name":["Master of Applied Science (MASc)"],"thesis:institution_name":["University of Ontario Institute of Technology"]},"updated_at":"2026-07-24T05:35:39Z"}