Optimal solution of the combined heat and power economic dispatch problem by adaptive fitness-distance balance based artificial rabbits optimization algorithm

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dc.authoridOzkaya, Burcin/0000-0002-9858-3982en_US
dc.authoridKAHRAMAN, Hamdi Tolga/0000-0001-9985-6324en_US
dc.authoridDuman, Serhat/0000-0002-1091-125Xen_US
dc.authorscopusid57199648907en_US
dc.authorscopusid35101845300en_US
dc.authorscopusid23389512500en_US
dc.authorscopusid25651286200en_US
dc.authorwosidOzkaya, Burcin/KLD-8092-2024en_US
dc.authorwosidKAHRAMAN, Hamdi Tolga/AAW-5335-2020en_US
dc.authorwosidDuman, Serhat/O-9406-2014en_US
dc.contributor.authorOzkaya, Burcin
dc.contributor.authorDuman, Serhat
dc.contributor.authorKahraman, Hamdi Tolga
dc.contributor.authorGuvenc, Ugur
dc.date.accessioned2024-08-23T16:04:46Z
dc.date.available2024-08-23T16:04:46Z
dc.date.issued2024en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractCombined heat and power economic dispatch (CHPED) problem is one of the most widely handled, optimization problem by researchers in modern power systems. CHPED problem is a complicated, non-continuous, and nonconvex optimization problem due to the constraints. Moreover, considering the valve-point loading effect (VPLE), transmission losses (TLs), and prohibited operating zones (POZs) of power-only units as constraints, the complexity of CHPED problem increases. Therefore, a powerful optimization algorithm needs to be introduced to find global solution that meets all constraints. In this paper, a novel adaptive fitness-distance balance based artificial rabbits optimization (AFDB-ARO) is developed to solve CHPED problems. AFDB-based guiding mechanism was implemented to enhance the exploration capability of ARO and to strengthen exploitation-exploration balance. A comprehensive experimental study was realized to prove the performance of the proposed algorithm on the CHPED and benchmark problems. In experimental study between AFDB-ARO variants and ARO on 40 benchmark problems, according to Wilcoxon analysis results, all AFDB-ARO variants outperformed the base ARO, and the best AFDB-ARO variant won victory in 20 of 40 problem and achieved similar results in other 20 problem. In other experimental study, AFDB-ARO algorithm was implemented on the CHPED systems with 4-, 5-, 7-, 24-, 48-, 96-, and 192-units, and fifteen case studies were considered using these systems, VPLE, TLs, and POZs. One of the important points of this study was that POZs were considered for the first time in 96-and 192 -units system. The results show that AFDB-ARO achieved the best optimal solution in ten of fifteen cases, was same in one case, and obtained almost same results in four cases compared to the literature. Moreover, the stability of the AFDB-ARO and base ARO algorithms in solving the CHPED problem were tested by performing stability analysis. While the mean success rate, mean iteration number, and mean search time were obtained 87.62%, 353.63, and 2.91 sec of AFDB-ARO, respectively, ARO managed to find the optimal solution in two cases. Thus, the superior performance of AFDB-ARO algorithm is confirmed by experimental studies and analysis against ARO algorithm. The source codes of the AFDB-ARO algorithm (proposed method) can be accessed at this link: https://www.mathworks.com/matlabcentral/fileexchange/136846-afdb-aro-an-improved-aro-algorithm-for-optimization-problem.en_US
dc.identifier.doi10.1016/j.eswa.2023.122272
dc.identifier.issn0957-4174
dc.identifier.issn1873-6793
dc.identifier.scopus2-s2.0-85175706449en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.eswa.2023.122272
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14359
dc.identifier.volume238en_US
dc.identifier.wosWOS:001111227800001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofExpert Systems With Applicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCombined heat and power economic dispatchen_US
dc.subjectLarge-scale systemsen_US
dc.subjectProhibited operating zonesen_US
dc.subjectAdaptive fitness distance balance baseden_US
dc.subjectartificial rabbits optimization algorithmen_US
dc.subjectStability analysisen_US
dc.subjectParticle Swarm Optimizationen_US
dc.subjectScale Combined Heaten_US
dc.subjectGroup Search Optimizationen_US
dc.subjectSolving Combined Heaten_US
dc.subjectGenetic Algorithmen_US
dc.subjectStrategyen_US
dc.titleOptimal solution of the combined heat and power economic dispatch problem by adaptive fitness-distance balance based artificial rabbits optimization algorithmen_US
dc.typeArticleen_US

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