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dc.contributor.authorAlcayde García, Alfredo
dc.contributor.authorBaños Navarro, Raúl
dc.contributor.authorArrabal Campos, Francisco Manuel
dc.contributor.authorGil Montoya, Francisco
dc.date.accessioned2020-01-20T08:29:43Z
dc.date.available2020-01-20T08:29:43Z
dc.date.issued2019-04-02
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/10835/7599
dc.description.abstractAn adequate selection of an energy provider and tariff requires us to analyze the different alternatives to choose one that satisfies your needs. In particular, choosing the right electricity tariff is essential for reducing company costs and improving competitiveness. This paper analyzes the energy consumption of large consumers that make intensive use of electricity and proposes the use of genetic algorithms for optimizing the tariff selection. The aim is to minimize electricity costs including two factors: the cost of power contracted and the heavy penalties for excess of power demand over the power contracted in certain time periods. In order to validate the proposed methodology, a case study based on the real data of energy consumption of a large Spanish university is presented. The results obtained show that the genetic algorithm and other bio-inspired approaches are able to reduce the costs associated to the electricity bill.es_ES
dc.language.isoenes_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectelectric power contractses_ES
dc.subjectelectric energy costses_ES
dc.subjectcost minimizationes_ES
dc.subjectevolutionary computationes_ES
dc.subjectbio-inspired algorithmses_ES
dc.titleOptimization of the Contracted Electric Power by Means of Genetic Algorithmses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionfile:///D:/Articulos/MDPI/energies-12-01270-v2.pdfes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional