Improved adaptive gaining-sharing knowledge algorithm with FDB-based guiding mechanism for optimization of optimal reactive power flow problem

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dc.authoridKAHRAMAN, Hamdi Tolga/0000-0001-9985-6324en_US
dc.authoridBakır, Hüseyin/0000-0001-5473-5158en_US
dc.authoridDuman, Serhat/0000-0002-1091-125Xen_US
dc.authoridguvenc, ugur/0000-0002-5193-7990en_US
dc.authorscopusid57216417848en_US
dc.authorscopusid35101845300en_US
dc.authorscopusid25651286200en_US
dc.authorscopusid23389512500en_US
dc.authorwosidKAHRAMAN, Hamdi Tolga/AAW-5335-2020en_US
dc.authorwosidBakır, Hüseyin/HMO-5183-2023en_US
dc.authorwosidguvenc, ugur/H-3029-2011en_US
dc.authorwosidDuman, Serhat/O-9406-2014en_US
dc.contributor.authorBakir, Huseyin
dc.contributor.authorDuman, Serhat
dc.contributor.authorGuvenc, Ugur
dc.contributor.authorKahraman, Hamdi Tolga
dc.date.accessioned2024-08-23T16:07:17Z
dc.date.available2024-08-23T16:07:17Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractOptimal reactive power flow (ORPF) is of great importance for the electrical reliability and economic operation of modern power systems. The integration of distributed generations (DGs) and two-terminal high voltage direct current (HVDC) systems into electrical networks has further complicated the ORPF problem. Due to the high computational complexity of the ORPF problem, a powerful and robust optimization algorithm is required to solve it. This paper proposes a powerful metaheuristic algorithm namely fitness-distance balance-based adaptive gaining-sharing knowledge (FDBAGSK). In the performance evaluation, 39 IEEE CEC benchmark functions are used to compare FDBAGSK with the original AGSK algorithm. Moreover, the proposed algorithm is applied to perform the ORPF task in modified IEEE 30- and IEEE 57-bus test systems. The effectiveness of the FDBAGSK method was tested for the optimization of three non-convex objectives: active power loss, voltage deviation and voltage stability index. The ORPF results obtained from the FDBAGSK algorithm are compared with other optimization algorithms in the literature. Given that all results are together, it has been observed that FDBAGSK is an effective method that can be used in solving global optimization and constrained real-world engineering problems.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK); [1649B031806288]en_US
dc.description.sponsorshipHueseyin Bakir would like to thank the support provided by Scientific and Technological Research Council of Turkey (TUBITAK) BIDEB 2211/A National PhD Scholarship Program under application number 1649B031806288.en_US
dc.identifier.doi10.1007/s00202-023-01803-9
dc.identifier.issn0948-7921
dc.identifier.issn1432-0487
dc.identifier.scopus2-s2.0-85160743489en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1007/s00202-023-01803-9
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14561
dc.identifier.wosWOS:000999201100002en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofElectrical Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFitness distance balance-based adaptive gaining-sharing knowledge algorithmen_US
dc.subjectOptimal reactive power flowen_US
dc.subjectHigh voltage direct currenten_US
dc.subjectDistributed generationsen_US
dc.subjectDispatchen_US
dc.subjectIntelligenceen_US
dc.subjectMethodologyen_US
dc.subjectTestsen_US
dc.titleImproved adaptive gaining-sharing knowledge algorithm with FDB-based guiding mechanism for optimization of optimal reactive power flow problemen_US
dc.typeArticleen_US

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