dc.creator | Ashley, Thomas Ian | es |
dc.creator | Carrizosa Priego, Emilio José | es |
dc.creator | Fernández Cara, Enrique | es |
dc.date.accessioned | 2019-02-11T08:10:15Z | |
dc.date.available | 2019-02-11T08:10:15Z | |
dc.date.issued | 2019-02-01 | |
dc.identifier.citation | Ashley, 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.issn | 0306-2619 | es |
dc.identifier.uri | https://hdl.handle.net/11441/82787 | |
dc.description.abstract | Soiling 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.sponsorship | Ministerio de Economía y Competitividad | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Applied Energy, 235 (1), 653-660. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Solar energy | es |
dc.subject | Routing problems | es |
dc.subject | Scheduling | es |
dc.subject | Cluster analysis | es |
dc.title | Heliostat field cleaning scheduling for Solar Power Tower plants: a heuristic approach | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Estadística e Investigación Operativa | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ecuaciones Diferenciales y Análisis Numérico | es |
dc.relation.projectID | PCIN-2015-108 | es |
dc.relation.projectID | MTM2015-65915-R | es |
dc.relation.publisherversion | https://reader.elsevier.com/reader/sd/pii/S0306261918317100?token=28670F6D48C0E220802957D9C5F1DFA9EA89FA1115D6686FFF99143A51D8F48BF3D70705F8F7C99B57D8F2ADC5D61DBC | es |
dc.identifier.doi | 10.1016/j.apenergy.2018.11.004 | es |
dc.contributor.group | Universidad de Sevilla. FQM329: Optimización | es |
dc.contributor.group | Universidad de Sevilla. FQM131: Ec.diferenciales, Simulación Num.y Desarrollo Software | es |
idus.format.extent | 8 p. | es |
dc.journaltitle | Applied Energy | es |
dc.publication.volumen | 235 | es |
dc.publication.issue | 1 | es |
dc.publication.initialPage | 653 | es |
dc.publication.endPage | 660 | es |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | |