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dc.creatorAshley, Thomas Ianes
dc.creatorCarrizosa Priego, Emilio Josées
dc.creatorFernández Cara, Enriquees
dc.date.accessioned2019-02-11T08:10:15Z
dc.date.available2019-02-11T08:10:15Z
dc.date.issued2019-02-01
dc.identifier.citationAshley, T.I., Carrizosa Priego, E.J. y Fernández Cara, E. (2019). Heliostat field cleaning scheduling for Solar Power Tower plants: a heuristic approach. Applied Energy, 235 (1), 653-660.
dc.identifier.issn0306-2619es
dc.identifier.urihttps://hdl.handle.net/11441/82787
dc.description.abstractSoiling of heliostat surfaces due to local climate has a direct impact on their optical efficiency and therefore a direct impact on the productivity of the Solar Power Tower plant. Cleaning techniques applied are dependent on plant construction and current schedules are normally developed considering heliostat layout patterns, providing sub-optimal results. In this paper, a method to optimise cleaning schedules is developed, with the objective of maximising energy generated by the plant. First, an algorithm finds a cleaning schedule by solving an integer program, which is then used as a starting solution in an exchange heuristic. Since the optimisation problems are of large size, a p-median type heuristic is performed to reduce the problem dimensionality by clustering heliostats into groups to be cleaned in the same period.es
dc.description.sponsorshipMinisterio de Economía y Competitividades
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofApplied Energy, 235 (1), 653-660.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectSolar energyes
dc.subjectRouting problemses
dc.subjectSchedulinges
dc.subjectCluster analysises
dc.titleHeliostat field cleaning scheduling for Solar Power Tower plants: a heuristic approaches
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Estadística e Investigación Operativaes
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ecuaciones Diferenciales y Análisis Numéricoes
dc.relation.projectIDPCIN-2015-108es
dc.relation.projectIDMTM2015-65915-Res
dc.relation.publisherversionhttps://reader.elsevier.com/reader/sd/pii/S0306261918317100?token=28670F6D48C0E220802957D9C5F1DFA9EA89FA1115D6686FFF99143A51D8F48BF3D70705F8F7C99B57D8F2ADC5D61DBCes
dc.identifier.doi10.1016/j.apenergy.2018.11.004es
dc.contributor.groupUniversidad de Sevilla. FQM329: Optimizaciónes
dc.contributor.groupUniversidad de Sevilla. FQM131: Ec.diferenciales, Simulación Num.y Desarrollo Softwarees
idus.format.extent8 p.es
dc.journaltitleApplied Energyes
dc.publication.volumen235es
dc.publication.issue1es
dc.publication.initialPage653es
dc.publication.endPage660es
dc.contributor.funderMinisterio de Economía y Competitividad (MINECO). España

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