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Diagnosis of a battery energy storage system based on principal component analysis

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Diagnosis of a battery energy storage system based on principal component analysis

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dc.contributor.author Banguero-Palacios, Edison es_ES
dc.contributor.author Correcher Salvador, Antonio es_ES
dc.contributor.author Pérez-Navarro Gómez, Ángel es_ES
dc.contributor.author García Moreno, Emilio es_ES
dc.contributor.author Aristizabal, Andrés es_ES
dc.date.accessioned 2021-07-01T03:32:17Z
dc.date.available 2021-07-01T03:32:17Z
dc.date.issued 2020-02 es_ES
dc.identifier.issn 0960-1481 es_ES
dc.identifier.uri http://hdl.handle.net/10251/168596
dc.description.abstract [EN] This paper proposes the use of principal component analysis (PCA) for the state of health (SOH) diagnosis of a battery energy storage system (BESS) that is operating in a renewable energy laboratory located in Chocó, Colombia. The presented methodology allows the detection of false alarms during the operation of the BESS. The principal component analysis model is applied to a parameter set associated to the capacity, internal resistance and open circuit voltage of a battery energy storage system. The parameters are identified from experimental data collected daily. The PCA model retains the first 5 components that collect 80.25% of the total variability. During the test under real operation contidions, PCA diagnosed a degradation of state of health fastest than the comercial battery controller. A change in the charging modes lead to a battery recovery that was also monitored by the proposed algortihm, and control actions are proposed that lead the BESS to work in normal conditions. es_ES
dc.description.sponsorship The authors would like to acknowledge the research project "Implementacion de un programa de desarrollo e investigacion de energias renovables en el departamento del Choco, BPIN 2013000100285 (in Spanish)" and the Universidad TecnolOgica del Choco (in Spanish). The authors would like to thank the anonymous reviewers as well as the editor for their valuable comments that have greatly improved the final version of the paper. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Renewable Energy es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Diagnosis es_ES
dc.subject Battery energy storage system es_ES
dc.subject Principal component analysis es_ES
dc.subject State of health es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.subject.classification INGENIERIA ELECTRICA es_ES
dc.title Diagnosis of a battery energy storage system based on principal component analysis es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.renene.2019.08.064 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Universidad Tecnológica del Chocó//BPIN 2013000100285/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto de Ingeniería Energética - Institut d'Enginyeria Energètica es_ES
dc.description.bibliographicCitation Banguero-Palacios, E.; Correcher Salvador, A.; Pérez-Navarro Gómez, Á.; García Moreno, E.; Aristizabal, A. (2020). Diagnosis of a battery energy storage system based on principal component analysis. Renewable Energy. 146:2438-2449. https://doi.org/10.1016/j.renene.2019.08.064 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.renene.2019.08.064 es_ES
dc.description.upvformatpinicio 2438 es_ES
dc.description.upvformatpfin 2449 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 146 es_ES
dc.relation.pasarela S\392513 es_ES
dc.contributor.funder Universidad Tecnológica del Chocó es_ES
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dc.subject.ods 07.- Asegurar el acceso a energías asequibles, fiables, sostenibles y modernas para todos es_ES


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