Scalable method for administration of resource technologies under stochastic procedures

dc.centroE.T.S.I. Telecomunicaciónes_ES
dc.contributor.authorMerino-Córdoba, Salvador
dc.contributor.authorMartínez-del-Castillo, Javier
dc.contributor.authorGuzmán-Navarro, Francisco
dc.contributor.authorSánchez-Pacheco, Francisco José
dc.contributor.authorGuzmán-Sepúlveda, Rafael
dc.contributor.authorSidrach-de-Cardona-Ortin, Mariano
dc.contributor.authorLara-Fernández, Juan de Dios
dc.date.accessioned2023-04-20T12:28:13Z
dc.date.available2023-04-20T12:28:13Z
dc.date.created2023-04-20
dc.date.issued2022-11-09
dc.departamentoMatemática Aplicada
dc.description.abstractDuring the development of the S3Unica project (Smart Specialisation University Campus) and its application in the ASSET project (Advanced Systems Studies for Energy Transition), both within the European Commission, the resolution of the distributed energy generation model was proposed through the creation of an algorithm that would allow the shared market between producers and consumers. From this premise arose the need to create a replicable system to resolve this situation in the new shared generation environment, using low-cost technologies. This work develops the scalable method for resource management technologies (SMART), based on stochastic procedures, which generates microgrids with an integrated energy market. The interest of this work is based on the incorporation of real-time analysis, applying stochastic methods, and its fusion with probabilistic predictive methods that evolve and harmonise the results. The fact that the process is self-learning also enables the use of metadomotic as a tool for both comfort improvement and energy sharing. The most important results developed were the design of the internal scheme of the low-cost SMART control device together with the developments of both individual and collective resolution algorithms. By achieving the incorporation of internal and external producers in the same numerical procedure, the distributed and hybrid generation models are solved simultaneously.es_ES
dc.description.sponsorshipWe thank the support of this paper from University of Malaga and CBUA (funding for open access charge: Universidad de Málaga / CBUA) and we thank also the anonymous reviewers whose suggestions helped improve and clarify this manuscript. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.es_ES
dc.identifier.citationMerino, S., Martínez, J., Guzmán, F., Sánchez, F. J., Guzmán, R., de Cardona, M. S., & Lara, J. D. (2023). Scalable method for administration of resource technologies under stochastic procedures. Applied Mathematics and Computation, 440, 127652.es_ES
dc.identifier.doihttps://doi.org/10.1016/j.amc.2022.127652
dc.identifier.urihttps://hdl.handle.net/10630/26326
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectIngeniería sosteniblees_ES
dc.subjectRecursos energéticos - Modelos matemáticoses_ES
dc.subject.otherScalabilityes_ES
dc.subject.otherDistributed generationes_ES
dc.subject.otherHybrid generationes_ES
dc.subject.otherSustainabilityes_ES
dc.subject.otherStochastices_ES
dc.titleScalable method for administration of resource technologies under stochastic procedureses_ES
dc.typejournal articlees_ES
dc.type.hasVersionVoRes_ES
dspace.entity.typePublication
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