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dc.contributor.authorCortés-Caicedo, Brandon
dc.contributor.authorMontoya, Oscar Danilo
dc.contributor.authorArias-Londoño, Andrés
dc.date.accessioned2023-07-21T15:41:17Z
dc.date.available2023-07-21T15:41:17Z
dc.date.issued2022
dc.date.submitted2023
dc.identifier.citationCortés-Caicedo, B.; Montoya, O.D.; Arias-Londoño, A. Application of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measures. Computers 2022, 11, 55. https://doi.org/10.3390/computers11040055spa
dc.identifier.urihttps://hdl.handle.net/20.500.12585/12275
dc.description.abstractIn this research paper, a combinatorial optimization approach is proposed for parameter estimation in single-phase transformers considering voltage and current measurements at the transformer terminals. This problem is represented through a nonlinear programming model (NLP), whose objective is to minimize the root mean square error between the measured voltage and current values and the calculated values from the equivalent model of the single-phase transformer. These values of voltage and current can be determined by applying Kirchhoff’s Laws to the model T of the transformer, where its parameters, series resistance and reactance as well as the magnetization resistance and reactance, i.e., R1, R′2,X1, X′2,Rc y Xm, are provided by the Hurricane Optimization Algorithm (HOA). The numerical results in the 4 kVA, 10 kVA and 15 kVA single-phase test transformers demonstrate the applicability of the proposed method since it allows the reduction of the average error between the measured and calculated electrical variables by 1000% compared to the methods reported in the specialized literature. This ensures that the parameters estimated by the proposed methodology, in each test transformer, are close to the real value with an accuracy error of less than 6%. Additionally, the computation times required by the algorithm to find the optimal solution are less than 1 second, which makes the proposed HOA robust, reliable, and efficient. All simulations were performed in the MATLAB programming environment. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.spa
dc.format.extent19 páginas
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceComputers 2022, 11, 55spa
dc.titleApplication of the Hurricane Optimization Algorithm to Estimate Parameters in Single-Phase Transformers Considering Voltage and Current Measuresspa
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datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.versionhttp://purl.org/coar/version/c_b1a7d7d4d402bccespa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasversioninfo:eu-repo/semantics/draftspa
dc.identifier.doihttps://doi.org/10.3390/computers11040055
dc.subject.keywordsTransformer Windings;spa
dc.subject.keywordsFrequency Response;spa
dc.subject.keywordsElectric Potentialspa
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
dc.type.spahttp://purl.org/coar/resource_type/c_6501spa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_6501spa


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