Development of a Levy flight and FDB-based coyote optimization algorithm for global optimization and real-world ACOPF problems

Basit Öğe Kaydı
dc.authoridDuman, Serhat/0000-0002-1091-125X
dc.authoridkahraman, hamdi/0000-0001-9985-6324
dc.authoridAras, Sefa/0000-0002-4043-3754
dc.authorwosidDuman, Serhat/O-9406-2014
dc.authorwosidkahraman, hamdi/N-5248-2014
dc.authorwosidAras, Sefa/V-9527-2017
dc.contributor.authorDuman, Serhat
dc.contributor.authorKahraman, Hamdi T.
dc.contributor.authorGuvenc, Ugur
dc.contributor.authorAras, Sefa
dc.date.accessioned2021-12-01T18:49:10Z
dc.date.available2021-12-01T18:49:10Z
dc.date.issued2021
dc.department[Belirlenecek]en_US
dc.description.abstractThis article presents an improved version of the coyote optimization algorithm (COA) that is more compatible with nature. In the proposed algorithm, fitness-distance balance (FDB) and Levy flight were used to determine the social tendency of coyote packs and to develop a more effective model imitating the birth of new coyotes. The balanced search performance, global exploration capability, and local exploitation ability of the COA algorithm were enhanced, and the premature convergence problem resolved using these two methods. The performance of the proposed Levy roulette FDB-COA (LRFDBCOA) was compared with 28 other meta-heuristic search (MHS) algorithms to verify its effectiveness on 90 benchmark test functions in different dimensions. The proposed LRFDBCOA and the COA ranked, respectively, the first and the ninth, according to nonparametric statistical results. The proposed algorithm was applied to solve the AC optimal power flow (ACOPF) problem incorporating thermal, wind, and combined solar-small hydro powered energy systems. This problem is described as a constrained, nonconvex, and complex power system optimization problem. The simulation results showed that the proposed algorithm exhibited a definite superiority over both the constrained and highly complex real-world engineering ACOPF problem and the unconstrained convex/nonconvex benchmark problems.en_US
dc.identifier.doi10.1007/s00500-021-05654-z
dc.identifier.endpage6617en_US
dc.identifier.issn1432-7643
dc.identifier.issn1433-7479
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-85102027544en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage6577en_US
dc.identifier.urihttps://doi.org/10.1007/s00500-021-05654-z
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10675
dc.identifier.volume25en_US
dc.identifier.wosWOS:000625039600003en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofSoft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectL&#233en_US
dc.subjectvy stepsen_US
dc.subjectFitness-distance balance (FDB)en_US
dc.subjectFDB-enhanced coyote optimization algorithm (FDB-COA)en_US
dc.subjectOptimal power flowen_US
dc.subjectRenewable energy sourcesen_US
dc.subjectModern power systemsen_US
dc.titleDevelopment of a Levy flight and FDB-based coyote optimization algorithm for global optimization and real-world ACOPF problemsen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
10675.pdf
Boyut:
3.75 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu