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DC Field | Value | Language |
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dc.rights.license | restrictedAccess | - |
dc.contributor.author | Ranković, Aleksandar | - |
dc.date.accessioned | 2021-04-20T18:39:24Z | - |
dc.date.available | 2021-04-20T18:39:24Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | https://scidar.kg.ac.rs/handle/123456789/11559 | - |
dc.description.abstract | Copyright © 2016 John Wiley & Sons, Ltd. This paper proposes a novel method for determining optimal arrangements of overhead double-circuit power line conductors aimed to reduce electric and magnetic field emissions. Extremely low frequency electric and magnetic field optimization problems have multiple objectives. Multiple-objective optimization allows the simultaneous optimization of two or more conflicting objectives and determination of mutually non-dominated solutions. The multi-objective optimization technique used in this paper is based on Genetic Algorithm to obtain a set of mutually non-dominated solutions (Pareto optimal set) for the two objectives: the electric and magnetic field strengths near overhead double-circuit power line. Also, additional assessment criteria were defined for the selection of several decision scenarios from the Pareto optimal set. The results and practical aspects of the proposed methodology are demonstrated on two typical 400-kV double-circuit overhead power lines. The efficiency of the proposed multiple-objective optimization method is compared with the existing one based on single-objective optimization function. Copyright © 2016 John Wiley & Sons, Ltd. | - |
dc.rights | info:eu-repo/semantics/restrictedAccess | - |
dc.source | International Transactions on Electrical Energy Systems | - |
dc.title | Novel multi-objective optimization method of electric and magnetic field emissions from double-circuit overhead power line | - |
dc.type | article | - |
dc.identifier.doi | 10.1002/etep.2243 | - |
dc.identifier.scopus | 2-s2.0-84979211058 | - |
Appears in Collections: | Faculty of Technical Sciences, Čačak |
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PaperMissing.pdf Restricted Access | 29.86 kB | Adobe PDF | View/Open |
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