A Comprehensive Analysis of Grid-Based Wind Turbine Layout Using an Efficient Binary Invasive Weed Optimization Algorithm With Levy Flight

dc.contributor.author Koç, İsmail
dc.date.accessioned 2022-05-23T20:23:43Z
dc.date.available 2022-05-23T20:23:43Z
dc.date.issued 2022
dc.description.abstract Wind energy has attracted great attention in recent years due to the increasing demand for alternative energy sources. Gathering the maximum amount of energy from wind energy is directly related to the layout of wind turbines in wind farm. This study focuses on grid-based wind turbine layout problem in an area of 2 km x 2 km. In order to solve this problem, 9 novel grids of 11 x 11, 12 x 12, ... and 19 x 19 are proposed in this paper in addition to 10 x 10 and 20 x 20 turbine grids which have already used in the literature. A new repair operator is recommended, taking into account the distance constraint between two adjacent cells in turbine layout problem, and thus the obtained solutions are made feasible. Furthermore, a levy flight-based IWO (LFIWO) algorithm is developed to optimize the layout of the turbines in wind farm. The basic IWO algorithm and the proposed LFIWO algorithm are compared on 11 different turbine layouts. Experimental studies are carried out for both algorithms under equal conditions with the help of 10 different binary versions. According to the comparisons performed using 11 different grids, LFIWO demonstrates a much superior success than the IWO algorithm. In addition, the proposed 19 x 19 grid reveals the best success among the other grids. When compared to the other studies in the literature, it is seen that LFIWO surpasses the other algorithms in terms of solution quality. As a result, it can be clearly stated that the proposed binary version of LFIWO is a competitive and effective binary algorithm. en_US
dc.identifier.doi 10.1016/j.eswa.2022.116835
dc.identifier.issn 0957-4174
dc.identifier.issn 1873-6793
dc.identifier.scopus 2-s2.0-85126125127
dc.identifier.uri https://doi.org/10.1016/j.eswa.2022.116835
dc.identifier.uri https://hdl.handle.net/20.500.13091/2495
dc.language.iso en en_US
dc.publisher Pergamon-Elsevier Science Ltd en_US
dc.relation.ispartof Expert Systems With Applications en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Invasive weed optimization en_US
dc.subject Levy flight en_US
dc.subject Wind turbine placement en_US
dc.subject Turbine layout en_US
dc.subject Binary algorithm en_US
dc.subject Particle Swarm Optimization en_US
dc.subject Farm Layout en_US
dc.subject Genetic Algorithm en_US
dc.subject Design Optimization en_US
dc.subject Optimal Placement en_US
dc.subject Power Production en_US
dc.subject Model en_US
dc.subject System en_US
dc.subject Mutation en_US
dc.title A Comprehensive Analysis of Grid-Based Wind Turbine Layout Using an Efficient Binary Invasive Weed Optimization Algorithm With Levy Flight en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.bip.impulseclass C4
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.description.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümü en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 116835
gdc.description.volume 198 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W4221122346
gdc.identifier.wos WOS:000792157000004
gdc.index.type WoS
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gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration National
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gdc.opencitations.count 11
gdc.plumx.crossrefcites 5
gdc.plumx.mendeley 23
gdc.plumx.scopuscites 19
gdc.scopus.citedcount 19
gdc.virtual.author Koç, İsmail
gdc.wos.citedcount 15
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