AC/DC power systems planning comprising voltage source converters using an enhanced symbiotic organisms search algorithm

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dc.contributor.authorBattal, Onur
dc.contributor.authorGüvenç, Uǧur
dc.date.accessioned2025-10-11T20:45:19Z
dc.date.available2025-10-11T20:45:19Z
dc.date.issued2025
dc.departmentDüzce Üniversitesien_US
dc.description.abstractThe concept of distributed energy, where different energy sources are combined in remote locations, forms the basis of today's power systems overall energy production logic. Furthermore, advancements in power electronic infrastructures have emphasized their increased utilization within power systems. In particular, the transition from current source converters (CSC) technology to voltage source converters (VSC) technology has made it easier to integrate power grids with different characteristics into existing power systems. High voltage direct current (HVDC) transmission applications also play a significant role in this integration. In these increasingly complex power systems with various infrastructures and applications, maintaining a sustainable, secure, economical, and environmentally-friendly balance between supply and demand becomes more challenging using classical approaches. In this study, a metaheuristic algorithm is proposed for solving the power flow problems in hybrid AC/DC power systems that include VSC-based, Multi-Terminal HVDC grids. The proposed algorithm is an enhanced version of the symbiotic organisms search (SOS) algorithm and is named di-SOS (diversity improved SOS with Parazite RFDB) algorithm. To demonstrate the effectiveness of the developed algorithm, comparisons were made with SOS algorithm variants and 15 different metaheuristic algorithms found in the literature using various test functions. Nonparametric Wilcoxon signed-rank tests and Friedman tests were performed the compared algorithms and in the comparison between SOS algorithm variants, the di_1-SOS variant of the di_SOS algorithm performed the best with an algorithm score of 2.245. In the comparison with the other 15 metaheuristic algorithms, the di_1-SOS algorithm ranked first with a ranking score of 4.525, demonstrating its success in solving classical test functions. Finally, the algorithm was employed to address power flow problems concerns within hybrid AC/DC power systems, employing altered instances of the IEEE 14-bus and IEEE 30-bus test networks. The acquired outcomes substantiated the efficacy of the algorithm in strategic formulation of AC/DC power systems and in resolving intricate real-world engineering problems, characterized by nonlinearities and constraints. © 2025 Elsevier B.V., All rights reserved.en_US
dc.identifier.doi10.1007/s00521-024-10722-0
dc.identifier.endpage2986en_US
dc.identifier.issn1433-3058
dc.identifier.issn0941-0643
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-85212035597en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage2945en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-024-10722-0
dc.identifier.urihttps://hdl.handle.net/20.500.12684/21271
dc.identifier.volume37en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofNeural Computing and Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKA_Scopus_20250911
dc.subjectDistance Balance (rfdb)en_US
dc.subjectEnhanced Sos Algorithm (di-sos)en_US
dc.subjectMeta Heuristic Searchen_US
dc.subjectMthvdcen_US
dc.subjectPower Flowen_US
dc.subjectRoulette Fitnessen_US
dc.subjectVscen_US
dc.subjectComputer Debuggingen_US
dc.subjectElectric Load Flowen_US
dc.subjectElectric Power System Planningen_US
dc.subjectElectric Power Transmission Networksen_US
dc.subjectGeophysical Prospectingen_US
dc.subjectGroundwater Resourcesen_US
dc.subjectHeuristic Methodsen_US
dc.subjectHvdc Power Transmissionen_US
dc.subjectMineral Explorationen_US
dc.subjectOverhead Linesen_US
dc.subjectPhosphate Depositsen_US
dc.subjectSalt Depositsen_US
dc.subjectSubjective Testingen_US
dc.subjectSulfur Depositsen_US
dc.subjectSurface Water Resourcesen_US
dc.subjectSurface Watersen_US
dc.subjectWater Wellsen_US
dc.subjectDistance Balanceen_US
dc.subjectDistance Balance (rfdb)en_US
dc.subjectEnhanced Symbiotic Organism Search Algorithm (di-symbiotic Organism Search)en_US
dc.subjectMeta-heuristic Searchen_US
dc.subjectMthvdcen_US
dc.subjectPower Flowsen_US
dc.subjectRoulette Fitnessen_US
dc.subjectSearch Algorithmsen_US
dc.subjectSymbioticsen_US
dc.subjectVoltage Sourceen_US
dc.subjectHeuristic Algorithmsen_US
dc.titleAC/DC power systems planning comprising voltage source converters using an enhanced symbiotic organisms search algorithmen_US
dc.typeArticleen_US

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