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Allocation of Renewable Energy Resources in Distribution Systems While considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithm

dc.contributor.authorZishan, Farhad
dc.contributor.authorMansouri, Saeedeh
dc.contributor.authorAbdollahpour
dc.contributor.authorGrisales-Noreña, Luis Fernando
dc.contributor.authorMontoya, Oscar Danilo
dc.date.accessioned2023-07-19T21:11:16Z
dc.date.available2023-07-19T21:11:16Z
dc.date.issued2023
dc.date.submitted2023
dc.identifier.citationZishan F, Mansouri S, Abdollahpour F, Grisales-Noreña LF, Montoya OD. Allocation of Renewable Energy Resources in Distribution Systems While considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithm. Energies. 2023; 16(1):474. https://doi.org/10.3390/en16010474spa
dc.identifier.urihttps://hdl.handle.net/20.500.12585/12169
dc.description.abstractGiven the importance of renewable energy sources in distribution systems, this article addresses the problem of locating and determining the capacity of these sources, namely, wind turbines and solar panels. To solve this optimization problem, a new algorithm based on the behavior of salp is used. The objective functions include reducing losses, improving voltage profiles, and reducing the costs of renewable energy sources. In this method, the allocation of renewable resources is considered for different load models in distribution systems and different load levels using smart meters. Due to the fact that these objective functions are multi-objective, the fuzzy decision-making method is used to select the optimal solution from the set of Pareto solutions. The considered objective functions lead to loss reduction, voltage profile improvement, and RES cost reduction (A allocating RES resources optimally without resource limitations; B: allocating RES resources optimally with resource limitations). In addition, daily wind, solar radiation, and temperature data are taken into account. The proposed method is applied to the IEEE standard 33-bus system. The simulation results show the better performance of the multi-objective salp swarm algorithm (MSSA) at improving voltage profiles and reducing losses in distribution systems. Lastly, the optimal results of the MSSA algorithm are compared with the PSO and GA algorithms. © 2023 by the authors.spa
dc.format.extent17 páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceEnergies Volume 16, Issue 1spa
dc.titleAllocation of Renewable Energy Resources in Distribution Systems While considering the Uncertainty of Wind and Solar Resources via the Multi-Objective Salp Swarm Algorithmspa
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datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
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dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasversioninfo:eu-repo/semantics/draftspa
dc.identifier.doi10.3390/en16010474
dc.subject.keywordsPlacement;spa
dc.subject.keywordsActive Distributionspa
dc.subject.keywordsNetwork;spa
dc.subject.keywordsVoltage Stabilityspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.ccAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.identifier.instnameUniversidad Tecnológica de Bolívarspa
dc.identifier.reponameRepositorio Universidad Tecnológica de Bolívarspa
dc.publisher.placeCartagena de Indiasspa
dc.subject.armarcLEMB
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