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dc.contributorEscuela de Ingenierias Industrial, Informática y Aeroespaciales_ES
dc.contributor.authorPagnini, Luisa Carlotta
dc.contributor.authorBracco, Stefano
dc.contributor.authorDelfino, Federico
dc.contributor.authorDe-simón-martín, Miguel
dc.contributor.otherIngenieria de Sistemas y Automaticaes_ES
dc.date2024
dc.date.accessioned2024-05-06T07:56:27Z
dc.date.available2024-05-06T07:56:27Z
dc.identifier.citationPagnini, L., Bracco, S., Delfino, F., & de-Simón-Martín, M. (2024). Levelized cost of electricity in renewable energy communities: Uncertainty propagation analysis. Applied Energy, 366, 123278. https://doi.org/10.1016/j.apenergy.2024.123278es_ES
dc.identifier.issn0306-2619
dc.identifier.urihttps://hdl.handle.net/10612/20353
dc.description.abstract[EN]Renewable Energy Communities (RECs) are being deployed all around the World as a technically feasible solution to decreasing users' dependence on fossil fuels. Several demonstration facilities have shown their potential to provide final consumers with clean energy and all associated environmental benefits. However, the economic evaluation of these systems as a whole set is more complex than evaluating generation technologies individually, which can be considered a barrier, and it may be more complicated to calculate its uncertainty with precision. This paper deals with this challenge and adapts a model for the evaluation of the global Levelized Cost of Electricity (LCOE) of a polygeneration microgrid to the characteristics of a typical REC, allowing the assessment of the distribution of the LCOE depending on the uncertainty of the input parameters. Thanks to its simple analytical formulation, the proposed model, that can be used for any combination of technologies (both renewable and conventional), provides relevant information on uncertainty propagation in a symbolic way that avoids the need to run numerical simulations or make assumptions on the distribution of the random input parameters. A case study has been presented, considering a typical small electrical REC with photovoltaic plants and micro wind turbines. Although the model can be defined to any market, as a representative example, it has been evaluated according to the current Spanish and Italian regulations, which are analyzed in depth with reference to the scientific literature. Results show that uncertainties in parameter estimates give rise to a very large scatter in the LCOE, pointing out a set of quantities whose role is crucial for a reliable estimate, among which electricity purchase and selling prices, yearly power load, and self-consumption / virtually-shared energy rates stand out.es_ES
dc.languageenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectIngeniería de sistemases_ES
dc.subject.otherLevelized Cost Of Electricityes_ES
dc.subject.otherRenewable Energy Communityes_ES
dc.subject.otherStatistical Analysises_ES
dc.subject.otherUncertainty Propagationes_ES
dc.titleLevelized cost of electricity in renewable energy communities: Uncertainty propagation analysises_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doi10.1016/j.apenergy.2024.123278
dc.description.peerreviewedSIes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleApplied Energyes_ES
dc.volume.number366es_ES
dc.page.initial123278es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES
dc.subject.unesco3301 Ingeniería y Tecnología Aeronáuticases_ES
dc.description.projectPublicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCLEes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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