The Arithmetic Optimization Algorithm for Optimal Energy Resource Planning

dc.authoridozdemir, aydogan/0000-0003-1331-2647
dc.authoridYounesi, Soheil/0000-0003-2170-857X
dc.authoridAhmadi, Bahman/0000-0002-1745-2228
dc.authorwosidozdemir, aydogan/A-2223-2016
dc.authorwosidAhmadi, Bahman/GSD-7380-2022
dc.contributor.authorCeylan, Oğuzhan
dc.contributor.authorYounesi, Soheil
dc.contributor.authorCeylan, Oguzhan
dc.contributor.authorOzdemir, Aydogan
dc.date.accessioned2023-10-19T15:11:50Z
dc.date.available2023-10-19T15:11:50Z
dc.date.issued2021
dc.department-temp[Ahmadi, Bahman; Younesi, Soheil; Ozdemir, Aydogan] Istanbul Tech Univ, Dept Elect Engn, Istanbul, Turkey; [Ceylan, Oguzhan] Kadir Has Univ, Management & Informat Syst Dept, Istanbul, Turkeyen_US
dc.description56th International Universities Power Engineering Conference (UPEC) - Powering Net Zero Emissions -- AUG 31-SEP 03, 2021 -- Teesside Univ, ELECTR NETWORKen_US
dc.description.abstractThis study presents a new formulation regarding optimal placement and sizing of multi-type distributed generations (DGs) and energy storage systems (ESSs) to enhance the reliability of a radial distribution system and to reduce the line losses employing Arithmetic Optimization Algorithm (AOA) method. The model determines the number of DGs and ESSs automatically, and is designed to minimize the losses and the reliability indices such as Customer Average Interruption Duration Index (CAIDI). The performance of the algorithm is tested on 69-bus radial distribution system. The objective functions corresponding to optimal type, location, and size of distributed energy resources are compared to the base-case values. Finally, a comparative performance analysis of the proposed algorithm is performed in terms of reliability indices and power losses with Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO).en_US
dc.description.sponsorshipIEEE,IEEE United Kingdom & Ireland Sect,IEEE Power & Energy Soc,Inst Engn & Technol,Lucas Nulle,MDPI, Elect Journal,MDPI, Energies Journalen_US
dc.description.sponsorshipTUBITAK [117E773]en_US
dc.description.sponsorshipThis research is funded as a part of 117E773 Advanced Evolutionary Computation for Smart Grid and Smart Community (TUBITAK) project under the framework of 1001 Project organized by TUBITAK.en_US
dc.identifier.citation8
dc.identifier.doi10.1109/UPEC50034.2021.9548204en_US
dc.identifier.isbn978-1-6654-4389-0
dc.identifier.scopus2-s2.0-85116614792en_US
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/UPEC50034.2021.9548204
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5241
dc.identifier.wosWOS:000723608400054en_US
dc.identifier.wosqualityN/A
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2021 56th International Universities Power Engineering Conference (Upec 2021): Powering Net Zero Emissionsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDistributed GenerationEn_Us
dc.subjectDistribution-SystemEn_Us
dc.subjectReliabilityEn_Us
dc.subjectReanalysisEn_Us
dc.subjectDistributed generation (DG)en_US
dc.subjectDistributed Generation
dc.subjectdistribution networks (DNs)en_US
dc.subjectDistribution-System
dc.subjectCustomer Average Interruption Duration Index (CAIDI)en_US
dc.subjectReliability
dc.subjectEnergy Not Supplied (ENS)en_US
dc.subjectReanalysis
dc.subjectOptimizationen_US
dc.titleThe Arithmetic Optimization Algorithm for Optimal Energy Resource Planningen_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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