Energy Loss Minimization with Parallel Implementation of Marine Predators Algorithm
dc.authorscopusid | 57226655033 | |
dc.authorscopusid | 57202848987 | |
dc.authorscopusid | 26665865200 | |
dc.authorscopusid | 7006505111 | |
dc.contributor.author | Ceylan, Oğuzhan | |
dc.contributor.author | Ahmadi, B. | |
dc.contributor.author | Ceylan, O. | |
dc.contributor.author | Ozdemir, A. | |
dc.date.accessioned | 2023-10-19T15:05:29Z | |
dc.date.available | 2023-10-19T15:05:29Z | |
dc.date.issued | 2021 | |
dc.department-temp | Younesi, 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, Turkey | en_US |
dc.description | 13th International Conference on Electrical and Electronics Engineering, ELECO 2021 --25 November 2021 through 27 November 2021 -- --176537 | en_US |
dc.description.abstract | Distribution 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.sponsorship | Türkiye Bilimsel ve Teknolojik Araştirma Kurumu, TÜBITAK | en_US |
dc.description.sponsorship | ACKNOWLEDGMENT 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.citation | 2 | |
dc.identifier.doi | 10.23919/ELECO54474.2021.9677829 | en_US |
dc.identifier.endpage | 72 | en_US |
dc.identifier.isbn | 9786050114379 | |
dc.identifier.scopus | 2-s2.0-85125226943 | en_US |
dc.identifier.scopusquality | N/A | |
dc.identifier.startpage | 67 | en_US |
dc.identifier.uri | https://doi.org/10.23919/ELECO54474.2021.9677829 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12469/4916 | |
dc.identifier.wosquality | N/A | |
dc.khas | 20231019-Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | 2021 13th International Conference on Electrical and Electronics Engineering, ELECO 2021 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | DG allocation problem | en_US |
dc.subject | Distribution networks | en_US |
dc.subject | Marine Predators Algorithm | en_US |
dc.subject | Parallel computing | en_US |
dc.subject | Smart grids | en_US |
dc.subject | Computational efficiency | en_US |
dc.subject | Electric power transmission networks | en_US |
dc.subject | Energy dissipation | en_US |
dc.subject | Smart power grids | en_US |
dc.subject | Allocation problems | en_US |
dc.subject | Distributed generator allocation problem | en_US |
dc.subject | Distributed generators | en_US |
dc.subject | Losses minimizations | en_US |
dc.subject | Marine predator algorithm | en_US |
dc.subject | Networks services | en_US |
dc.subject | Parallel com- puting | en_US |
dc.subject | Parallel Computation | en_US |
dc.subject | Parallel implementations | en_US |
dc.subject | Smart grid | en_US |
dc.subject | Heuristic methods | en_US |
dc.title | Energy Loss Minimization with Parallel Implementation of Marine Predators Algorithm | en_US |
dc.type | Conference Object | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | b80c3194-906c-4e78-a54c-e3cd1effc970 | |
relation.isAuthorOfPublication.latestForDiscovery | b80c3194-906c-4e78-a54c-e3cd1effc970 |
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