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Optimized design method for storage systems in photovoltaic plants with delivery limitation

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dc.contributor.authorColmenar Santos, Antonio
dc.contributor.authorMario Monteagudo Mencucci
dc.contributor.authorEnrique Rosales-Asensio
dc.contributor.authorMiguel de Simón Martín
dc.contributor.authorPérez Molina, Clara María
dc.date.accessioned2024-12-19T07:57:33Z
dc.date.available2024-12-19T07:57:33Z
dc.date.issued2019-03-01
dc.descriptionEsta es la versión aceptada para su publicación en Solar Energy, Volume 180, 2019, Pages 468-488. La versión final publicada está disponible en: https://doi.org/10.1016/j.solener.2019.01.046. This is the version accepted for publication in Solar Energy, Volume 180, 2019, Pages 468-488. The final published version is available at: https://doi.org/10.1016/j.solener.2019.01.046
dc.description.abstractIt results widely common for distribution network operators to impose restrictions on delivered solar photovoltaic generated power when the power plant rated power is greater than the maximum allowed due to the distribution network capacity. Thus, a feasible solution to maximize the performance of the solar power plant is the integration of battery energy storage systems. Although this configuration has been extensively studied in the existing literature, an optimal design method to determine the proper size and operation of the energy storage system needs to be developed. In this paper, a novel method to help power plants designers to determine the optimal battery energy storage capacity to integrate into any solar photovoltaic power plant is provided. The proposed algorithm minimizes the potential power curtailment and optimizes the utilization rate of the batteries storage system. The algorithm can be applied to any grid connected solar photovoltaic power plant under delivery power restrictions, regardless of power capacity and location. The algorithm has been implemented to a simulated power plant with delivery limitations based in a real case, and results with the optimal battery capacity show that the system would be able to recover up to the 83% of the curtailed energy and a yearly average capacity utilization of 56%. Moreover, the BESS operation has been validated with a scaled model run in Simulink and laboratory measurements, achieving 98% of curtailed energy recovery rate and a 57% of average capacity utilization.en
dc.description.versionversión final
dc.identifier.citationAntonio Colmenar-Santos, Mario Monteagudo-Mencucci, Enrique Rosales-Asensio, Miguel de Simón-Martín, Clara Pérez-Molina, Optimized design method for storage systems in photovoltaic plants with delivery limitation, Solar Energy, Volume 180, 2019, Pages 468-488, ISSN 0038-092X, https://doi.org/10.1016/j.solener.2019.01.046.
dc.identifier.doihttps://doi.org/10.1016/j.solener.2019.01.046
dc.identifier.issn0038-092X
dc.identifier.urihttps://hdl.handle.net/20.500.14468/24984
dc.journal.titleSolar Energy
dc.journal.volume180
dc.language.isoen
dc.page.final488
dc.page.initial468
dc.publisherElsevier
dc.relation.centerFacultades y escuelas::E.T.S. de Ingenieros Industriales
dc.relation.departmentIngeniería Eléctrica, Electrónica, Control, Telemática y Química Aplicada a la Ingeniería
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject33 Ciencias Tecnológicas
dc.subject.keywordsRenewable energy storageen
dc.subject.keywordsphotovoltaic solar energyen
dc.subject.keywordssystem optimizationen
dc.subject.keywordsbattery capacityen
dc.titleOptimized design method for storage systems in photovoltaic plants with delivery limitationen
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
person.familyNameColmenar Santos
person.familyNamePérez Molina
person.givenNameAntonio
person.givenNameClara María
person.identifier.orcid0000-0001-8543-4550
person.identifier.orcid0000-0001-8260-4155
relation.isAuthorOfPublication46632e74-cbcb-4861-8ffb-b8b7ba55284f
relation.isAuthorOfPublication5b060333-a864-4fd5-b494-4726487f4ba6
relation.isAuthorOfPublication.latestForDiscovery46632e74-cbcb-4861-8ffb-b8b7ba55284f
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