Combined heat and power economic emission dispatch using dynamic switched crowding based multi-objective symbiotic organism search algorithm

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dc.authoridKAHRAMAN, Hamdi Tolga/0000-0001-9985-6324en_US
dc.authoridOzkaya, Burcin/0000-0002-9858-3982en_US
dc.authorscopusid57199648907en_US
dc.authorscopusid23389512500en_US
dc.authorscopusid35101845300en_US
dc.authorscopusid25651286200en_US
dc.authorscopusid57227257300en_US
dc.authorwosidDuman, Serhat/O-9406-2014en_US
dc.authorwosidKAHRAMAN, Hamdi Tolga/AAW-5335-2020en_US
dc.authorwosidOzkaya, Burcin/KLD-8092-2024en_US
dc.contributor.authorOzkaya, Burcin
dc.contributor.authorKahraman, Hamdi Tolga
dc.contributor.authorDuman, Serhat
dc.contributor.authorGuvenc, Ugur
dc.contributor.authorAkbel, Mustafa
dc.date.accessioned2024-08-23T16:04:57Z
dc.date.available2024-08-23T16:04:57Z
dc.date.issued2024en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractCombined heat and power economic emission dispatch (CHPEED) problem is a highly complex, non-linear, non -convex multiobjective optimization problem due to two conflicting objectives and various operational constraints such as valve-point loading effect, power transmission loss, prohibited operating zone, and the feasible operating region of combined heat and power unit. In order to overcome these challenges, it is necessary to design an algorithm that exhibits a search behavior, which is suitable for the characteristics of objective and constraint space of the CHPEED problem. For these reasons, a dynamic switched crowding based multi-objective symbiotic organism search (DSC-MOSOS) algorithm was designed to meet the requirements and geometric space of the CHPEED problem. By applying the DSC method in the MOSOS algorithm, it was aimed to improve the exploration ability, to strengthen exploitation-exploration balance, and to prevent the catching into local solution traps. A comprehensive experimental study was carried out to prove the performance of the proposed al-gorithm on IEEE CEC 2020 multi-modal multi-objective problems (MMOPs) and CHPEED problem. In the experimental study conducted among eleven versions of MOSOS variations created with DSC-method and the base MOSOS algorithm on IEEE CEC 2020 MMOPs, according to Friedman scores based on the four performance metrics, the base MOSOS algorithm ranked the last. In other experimental study, the best DSC-MOSOS variant was applied to solve the CHPEED problem, where 5-, 7-, 10-and 14-unit test systems and eight case studies were considered. The important points of this study were that 10-unit and 14-unit test systems were presented to the literature, and the prohibited operating zone was considered in CHPEED problem for the first time. According to the results obtained from eight case studies obtained from the DSC-MOSOS and fourteen competitor algorithms, while the improvement in cost was between 0.2% and 16.55%, the reduction of the emission value was between 0.2 kg and 42.97 kg compared to the competitor algorithms. On the other hand, the stability of the DSC-MOSOS and the base MOSOS was evaluated using stability analysis. While the MOSOS algorithms was not able to perform a success in any case study, the DSC-MOSOS was achieved an average success rate with 91.16%. Thus, the performance of the DSC-MOSOS over the MOSOS was verified by the results of experimental studies and analysis.en_US
dc.identifier.doi10.1016/j.asoc.2023.111106
dc.identifier.issn1568-4946
dc.identifier.issn1872-9681
dc.identifier.scopus2-s2.0-85180373322en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2023.111106
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14416
dc.identifier.volume151en_US
dc.identifier.wosWOS:001146673900001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofApplied Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCombined heat and poweren_US
dc.subjectEconomic emission dispatchen_US
dc.subjectMulti-objective optimizationen_US
dc.subjectDynamic switched crowding (DSC)en_US
dc.subjectMulti-objective symbiotic organism search (MOSOS)en_US
dc.subjectEvolutionary Algorithmen_US
dc.subjectGenetic Algorithmen_US
dc.subjectOptimizationen_US
dc.titleCombined heat and power economic emission dispatch using dynamic switched crowding based multi-objective symbiotic organism search algorithmen_US
dc.typeArticleen_US

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