Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/106954
DC FieldValueLanguage
dc.contributor.authorColmenar-Santos, Antonioen_US
dc.contributor.authorMonteagudo-Mencucci, Marioen_US
dc.contributor.authorRosales Asensio, Enriqueen_US
dc.contributor.authorde Simón-Martín, Miguelen_US
dc.contributor.authorPérez-Molina, Claraen_US
dc.date.accessioned2021-04-22T08:32:27Z-
dc.date.available2021-04-22T08:32:27Z-
dc.date.issued2019en_US
dc.identifier.issn0038-092Xen_US
dc.identifier.urihttp://hdl.handle.net/10553/106954-
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_US
dc.languageengen_US
dc.relation.ispartofSolar Energyen_US
dc.sourceSolar Energy [ISSN 0038-092X], n. 180, p. 468-488 (marzo 2019)en_US
dc.subject332205 Fuentes no convencionales de energíaen_US
dc.subject.otherRenewable energy storageen_US
dc.subject.otherPhotovoltaic solar energyen_US
dc.subject.otherSystem optimizationen_US
dc.subject.otherBattery capacityen_US
dc.titleOptimized design method for storage systems in photovoltaic plants with delivery limitationen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.identifier.doi10.1016/j.solener.2019.01.046en_US
dc.description.lastpage488en_US
dc.description.firstpage468en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.description.numberofpages21en_US
dc.utils.revisionen_US
dc.identifier.ulpgcNoen_US
dc.contributor.buulpgcBU-INGen_US
dc.description.sjr1,537
dc.description.jcr4,608
dc.description.sjrqQ1
dc.description.jcrqQ2
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR Group for the Research on Renewable Energy Systems-
crisitem.author.deptDepartamento de Ingeniería Eléctrica-
crisitem.author.orcid0000-0003-4112-5259-
crisitem.author.parentorgDepartamento de Ingeniería Mecánica-
crisitem.author.fullNameRosales Asensio, Enrique-
Appears in Collections:Artículos
Show simple item record

WEB OF SCIENCETM
Citations

13
checked on Nov 17, 2024

Page view(s)

81
checked on Jun 1, 2024

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.