The Arithmetic Optimization Algorithm for Optimal Energy Resource Planning

dc.authorid ozdemir, aydogan/0000-0003-1331-2647
dc.authorid Younesi, Soheil/0000-0003-2170-857X
dc.authorid Ahmadi, Bahman/0000-0002-1745-2228
dc.authorwosid ozdemir, aydogan/A-2223-2016
dc.authorwosid Ahmadi, Bahman/GSD-7380-2022
dc.contributor.author Ahmadi, Bahman
dc.contributor.author Ceylan, Oğuzhan
dc.contributor.author Younesi, Soheil
dc.contributor.author Ceylan, Oguzhan
dc.contributor.author Ozdemir, Aydogan
dc.contributor.other Management Information Systems
dc.date.accessioned 2023-10-19T15:11:50Z
dc.date.available 2023-10-19T15:11:50Z
dc.date.issued 2021
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, Turkey en_US
dc.description 56th International Universities Power Engineering Conference (UPEC) - Powering Net Zero Emissions -- AUG 31-SEP 03, 2021 -- Teesside Univ, ELECTR NETWORK en_US
dc.description.abstract This 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.sponsorship IEEE,IEEE United Kingdom & Ireland Sect,IEEE Power & Energy Soc,Inst Engn & Technol,Lucas Nulle,MDPI, Elect Journal,MDPI, Energies Journal en_US
dc.description.sponsorship TUBITAK [117E773] en_US
dc.description.sponsorship This 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.citationcount 8
dc.identifier.doi 10.1109/UPEC50034.2021.9548204 en_US
dc.identifier.isbn 978-1-6654-4389-0
dc.identifier.scopus 2-s2.0-85116614792 en_US
dc.identifier.uri https://doi.org/10.1109/UPEC50034.2021.9548204
dc.identifier.uri https://hdl.handle.net/20.500.12469/5241
dc.identifier.wos WOS:000723608400054 en_US
dc.khas 20231019-WoS en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartof 2021 56th International Universities Power Engineering Conference (Upec 2021): Powering Net Zero Emissions en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 9
dc.subject Distributed Generation
dc.subject Distribution-System
dc.subject Distributed Generation En_Us
dc.subject Reliability
dc.subject Distribution-System En_Us
dc.subject Distributed generation (DG) en_US
dc.subject distribution networks (DNs) en_US
dc.subject Reliability En_Us
dc.subject Customer Average Interruption Duration Index (CAIDI) en_US
dc.subject Reanalysis
dc.subject Energy Not Supplied (ENS) en_US
dc.subject Reanalysis En_Us
dc.subject Optimization en_US
dc.title The Arithmetic Optimization Algorithm for Optimal Energy Resource Planning en_US
dc.type Conference Object en_US
dc.wos.citedbyCount 8
dspace.entity.type Publication
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