Energy Loss Minimization with Parallel Implementation of Marine Predators Algorithm

dc.authorscopusid57226655033
dc.authorscopusid57202848987
dc.authorscopusid26665865200
dc.authorscopusid7006505111
dc.contributor.authorCeylan, Oğuzhan
dc.contributor.authorAhmadi, B.
dc.contributor.authorCeylan, O.
dc.contributor.authorOzdemir, A.
dc.date.accessioned2023-10-19T15:05:29Z
dc.date.available2023-10-19T15:05:29Z
dc.date.issued2021
dc.department-tempYounesi, S., Istanbul Technical University, Department of Electrical Engineering, Istanbul, Turkey; Ahmadi, B., Istanbul Technical University, Department of Electrical Engineering, Istanbul, Turkey; Ceylan, O., Kadir Has University, Management and Information Systems Department, Istanbul, Turkey; Ozdemir, A., Istanbul Technical University, Department of Electrical Engineering, Istanbul, Turkeyen_US
dc.description13th International Conference on Electrical and Electronics Engineering, ELECO 2021 --25 November 2021 through 27 November 2021 -- --176537en_US
dc.description.abstractDistribution network (DN) service continuity is one of the significant issues in today's power systems. This paper aims to put a strategy for supplying loads with less discontinuity and affordable energy-consuming. The energy loss in distribution grids causes many problems for the producer and consumer; hence, it needs to be improved to increase supply efficiency accordingly. For this aim a model aiming to minimize power losses by allocating and sizing distributed generators (DGs) is solved using recently developed Marine Predators Algorithm (MPA). Since the proposed method is a time-intensive process due to the vast computations, parallel computation is implemented into MPA to increase computation speed. The proposed formulation and parallel computation are tested for 69-bus radial distribution system. The results are discussed in terms of computational accuracy and solution efficiency. Moreover, the convergence characteristics of MPA are compared with some other heuristic methods. © 2021 Chamber of Turkish Electrical Engineers.en_US
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAKen_US
dc.description.sponsorshipACKNOWLEDGMENT This research is funded as a part of “117E773 Advanced Evolutionary Computation for Smart Grid and Smart Community” project under the framework of 1001 Project organized by “The Scientific and Technological Research Council of Turkey TUBITAK”.en_US
dc.identifier.citation2
dc.identifier.doi10.23919/ELECO54474.2021.9677829en_US
dc.identifier.endpage72en_US
dc.identifier.isbn9786050114379
dc.identifier.scopus2-s2.0-85125226943en_US
dc.identifier.scopusqualityN/A
dc.identifier.startpage67en_US
dc.identifier.urihttps://doi.org/10.23919/ELECO54474.2021.9677829
dc.identifier.urihttps://hdl.handle.net/20.500.12469/4916
dc.identifier.wosqualityN/A
dc.khas20231019-Scopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2021 13th International Conference on Electrical and Electronics Engineering, ELECO 2021en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDG allocation problemen_US
dc.subjectDistribution networksen_US
dc.subjectMarine Predators Algorithmen_US
dc.subjectParallel computingen_US
dc.subjectSmart gridsen_US
dc.subjectComputational efficiencyen_US
dc.subjectElectric power transmission networksen_US
dc.subjectEnergy dissipationen_US
dc.subjectSmart power gridsen_US
dc.subjectAllocation problemsen_US
dc.subjectDistributed generator allocation problemen_US
dc.subjectDistributed generatorsen_US
dc.subjectLosses minimizationsen_US
dc.subjectMarine predator algorithmen_US
dc.subjectNetworks servicesen_US
dc.subjectParallel com- putingen_US
dc.subjectParallel Computationen_US
dc.subjectParallel implementationsen_US
dc.subjectSmart griden_US
dc.subjectHeuristic methodsen_US
dc.titleEnergy Loss Minimization with Parallel Implementation of Marine Predators Algorithmen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublicationb80c3194-906c-4e78-a54c-e3cd1effc970
relation.isAuthorOfPublication.latestForDiscoveryb80c3194-906c-4e78-a54c-e3cd1effc970

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