Developing temporal clustering for identifying solar radiation zones to improve separation models

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dc.article.number123809
dc.catalogadorcarga
dc.contributor.authorRodriguez, E.
dc.contributor.authorCardemil Iglesias, Jose Miguel
dc.contributor.authorDroguett, E.L.
dc.date.accessioned2025-07-30T11:03:25Z
dc.date.available2025-07-30T11:03:25Z
dc.date.issued2026
dc.description.abstract© 2025 Elsevier LtdAccurate solar-plant design requires detailed measurement campaigns to determine the site's radiative conditions. In the absence of empirical data, researchers employ separation models to estimate solar radiation components by calibrating polynomial coefficients with local meteorological data. Previous studies have adjusted these coefficients for various climate zones using the Köppen & Geiger classification, originally devised to demarcate regions based on plant distributions. Consequently, applying this classification to solar radiation may merge areas with different radiative characteristics, resulting in flawed assessments. This study describes a clustering technique that treats solar radiation as temporal data through the Discrete Fourier Transform and the Time Series Feature Extraction Library. By selecting input variables based on atmospheric attenuation and sky conditions, the K-means algorithm identified six clusters as the optimal solution, validated with a widely used separation model adjusted for the new clusters. The results of the estimation for the Cluster-adjusted model were then compared to the same separation model adjusted to the Köppen & Geiger classification. The Cluster-adjusted model showed superior performance in 34 of 50 stations, which shows that grouping meteorological stations according to their radiative characteristics achieves better results than dividing them on the basis of climate.
dc.description.funderANID
dc.description.funderSERC
dc.description.funderSubdirección de Capital Humano
dc.description.funderFONDAP
dc.description.funderFONDAP
dc.description.funderDoctorado Nacional
dc.fechaingreso.objetodigital2025-09-12
dc.fuente.origenScopus
dc.identifier.doi10.1016/j.renene.2025.123809
dc.identifier.eisbn978-3031497339
dc.identifier.eissn2317-6377
dc.identifier.isbn978-3031497322
dc.identifier.issn18790682 09601481
dc.identifier.pubmedidMEDLINE:32061311
dc.identifier.scopusidSCOPUS_ID:105009625680
dc.identifier.urihttps://doi.org/10.1016/j.renene.2025.123809
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/105071
dc.identifier.wosidWOS:001501512200001
dc.information.autorucEscuela de Ingeniería; Cardemil Iglesias Jose Miguel; 0000-0002-9022-8150; 119912
dc.issue.numeroPart A
dc.language.isoen
dc.nota.accesoContenido parcial
dc.publisherPalgrave Macmillan, Cham
dc.relation.ispartofGleizer, D., Kahan, E., Siman, Y. (eds) The Holocaust and Latin America. The Holocaust and its Contexts
dc.revistaRenewable Energy
dc.rightsacceso restringido
dc.subjectClustering
dc.subjectSeparation model
dc.subjectSolar irradiance
dc.subjectTemporal features extraction
dc.subject.ddc710
dc.subject.deweyArquitecturaes_ES
dc.titleDeveloping temporal clustering for identifying solar radiation zones to improve separation models
dc.typeartículo
dc.volumen256
sipa.codpersvinculados119912
sipa.indexScopus
sipa.trazabilidadWOS-SCOPUS;2025-07-30
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