Reliability evaluation in smart grids via modified Monte Carlo simulation method

dc.authorscopusid57193868250
dc.authorscopusid6603175851
dc.authorscopusid56826062200
dc.authorscopusid57193870627
dc.authorwosidABG-8088-2020
dc.authorwosidV-5463-2019
dc.authorwosidAAU-2662-2020
dc.authorwosidAAE-8198-2020
dc.contributor.authorWadi, Mohammed
dc.contributor.authorBaysal, Mustafa
dc.contributor.authorShobole, Abdulfetah
dc.contributor.authorTur, Mehmet Rıda
dc.contributor.authorWadi, Mohammed
dc.contributor.authorShobole, Abdulfetah Abdela
dc.date.accessioned2019-08-31T12:10:23Z
dc.date.accessioned2019-08-13T09:37:37Z
dc.date.available2019-08-31T12:10:23Z
dc.date.available2019-08-13T09:37:37Z
dc.date.issued2018en_US
dc.departmentMühendislik ve Doğa Bilimleri Fakültesien_US
dc.description7th International Conference on Renewable Energy Research and Applications (ICRERA) -- OCT 14-17, 2018 -- Paris, FRANCEen_US
dc.descriptionWOS: 000457681100134en_US
dc.description.abstractOperation of closed-ring power distribution systems has various advantages over both meshed-operated and radially-operated systems. Closed-ring system unlike to radial system, the voltage drop is less, achieves high reliability of power on demand since the power is supplied from both ends, and reduces the voltage fluctuation in high loaded areas by using a tie power line. However, the reliability assessment of closed-ring power grids is not a trivial task. Monte Carlo Simulation (MCS) is one of the most famous methods to assess the availability of any power system. However, the most proposed methods are able to evaluate the reliability of radial and open-ring grids. This paper developed the best known MCS method to assess the reliability of closed-ring grids by integrating the total loss of continuity (TLOC) definition into the MCS. The developed method is called modified Monte Carlo Simulation (MMCS) method. The MMCS is tested by using Roy Billinton Test System (RBTS) buses 2 and 4. The obtained results confirm the correctness of the proposed method. Therefore, MMCS method is appropriate to assess the reliability of both simple and complicated closed-ring systems.en_US
dc.description.sponsorshipInt Journal Renewable Energy Res, IJSmartGrid, IEEE, IEEE Ind Applicat Soc, IES, TMEIC, Isahaya Elect Corpen_US
dc.identifier.citationWadi, M., Baysal, M., Shobole, A., & Tur, M. R.. (2018). Reliability Evaluation in Smart Grids via Modified Monte Carlo Simulation Method. https://doi.org/10.1109/icrera.2018.8566982
dc.identifier.endpage845en_US
dc.identifier.isbn978-1-5386-5982-3
dc.identifier.issn2377-6897
dc.identifier.orcidAbdulfetah Shobol |0000-0002-3180-6504
dc.identifier.orcidMohammed Wadi |0000-0001-8928-3729
dc.identifier.orcidMehmet Rida Tür |0000-0001-5688-4624
dc.identifier.orcidMustafa Baysal |0000-0002-6298-918X
dc.identifier.scopus2-s2.0-85060658487
dc.identifier.scopusqualityN/A
dc.identifier.startpage841en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12436/968
dc.identifier.wosWOS: 000457681100134
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorWadi, Mohammed
dc.institutionauthorShobole, Abdulfetah
dc.language.isoen
dc.publisherIEEEen_US
dc.relation.ispartof2018 7th International Conference on Renewable Energy Research and Applications (ICRERA)en_US
dc.relation.ispartofseriesInternational Conference on Renewable Energy Research and Applications
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPower system reliabilityen_US
dc.subjectsmart power grids reliabilityen_US
dc.subjecttotal loss of continuity (TLOC)en_US
dc.subjectmodified Monte Carlo simulation method (MMCS)en_US
dc.titleReliability evaluation in smart grids via modified Monte Carlo simulation methoden_US
dc.typeConference Object
dspace.entity.typePublication
relation.isAuthorOfPublicatione57e2394-09f4-4128-bdb4-84c708867a9f
relation.isAuthorOfPublication4fd5b879-7f50-4336-a18f-5f6e6c324855
relation.isAuthorOfPublication.latestForDiscoverye57e2394-09f4-4128-bdb4-84c708867a9f

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