Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/14806
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dc.contributor.authorKivanc, Sercan-
dc.contributor.authorDeliismail, Ozgun-
dc.contributor.authorSildir, Hasan-
dc.date.accessioned2024-09-24T15:55:56Z-
dc.date.available2024-09-24T15:55:56Z-
dc.date.issued2024-
dc.identifier.issn2405-8963-
dc.identifier.urihttps://doi.org/10.1016/j.ifacol.2024.07.089-
dc.descriptionInternational Federation of Automatic Control (IFAC) - Modelling and Control of Environmental Systems, TC 8.3; International Federation of Automatic Control (IFAC) - TC 6.3. Power and Energy Systemsen_US
dc.description.abstractWith increased energy demand as it gets scarcer, a great deal of research is being carried out into alternatives to non - renewable energy resources. One of the promising studies is the biofuel production from micro algae. Microalgae are photosynthetic organisms and capture carbon dioxide, reducing emissions and providing valuable products (fuel, fertilizer, etc.). Thus, efficiency in the design and optimization of process related units are important. In this study, the optimal experimental conditions for Nannochloropsis Oculata were calculated under the constraints of the model equations and other process related constraints through simultaneous optimization approach. The economic evaluation of the process is also handled by introducing the uncertainty in the economic measures sampled from normal distribution to maximize the average profit. Unlike traditional approaches, the MINLP formulation, which is solved stochastically, dynamically, and simultaneously, provides more robust and reliable results, flexibility, improved decision making, reduced risks to be taken and a better understanding of risk factors. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartof3rd IFAC Workshop on Integrated Assessment Modeling for Environmental Systems (IAMES) -- MAY 29-31, 2024 -- Savona, ITALYen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectStochastic Optimizationen_US
dc.subjectMINLPen_US
dc.subjectDynamic Optimizationen_US
dc.titleA Mixed-Integer Dynamic and Stochastic Algae Process Optimizationen_US
dc.typeConference Objecten_US
dc.departmentIzmir Institute of Technologyen_US
dc.identifier.volume58en_US
dc.identifier.issue2en_US
dc.identifier.startpage44en_US
dc.identifier.endpage48en_US
dc.identifier.wosWOS:001295980100008-
dc.identifier.scopus2-s2.0-85201799699-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.ifacol.2024.07.089-
dc.authorscopusid59294447800-
dc.authorscopusid57191163671-
dc.authorscopusid55005950400-
dc.identifier.scopusqualityQ3-
dc.description.woscitationindexConference Proceedings Citation Index - Science-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeConference Object-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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