1. Ktisis Cyprus University of Technology
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Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/19220
DC FieldValueLanguage
dc.contributor.authorStylianou, Stavros-
dc.contributor.authorTapakis, Rogiros-
dc.contributor.authorCharalambides, Alexandros G.-
dc.date.accessioned2020-10-20T11:16:13Z-
dc.date.available2020-10-20T11:16:13Z-
dc.date.issued2020-10-20-
dc.identifier.citationInternational Journal of Sustainable Energy, 2020, vol. 39, no. 9, pp. 880-895en_US
dc.identifier.issn14786451-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/19220-
dc.description.abstractThe current study evaluates a new method for the estimation of cloud cover using only photovoltaics (PV) as ground-based irradiance sensors. Seven different scenarios were examined using 30, 50, 75, 100, 500 and 1000 randomly and 1000 non-randomly distributed residential PV stations in a study area of 10 km × 10 km For each scenario, 3500 different fractal-based cloud shadows were produced and the accuracy of the model in estimating the cloud cover, in percentage cover and in oktas, based on the number of stations being shaded, was calculated. With 30 PV stations, the model produced an average accuracy of only 57% for the predicted okta cover, while its accuracy increased to 90% and 94% with 500 and 1000 PV stations.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Sustainable Energyen_US
dc.rights© The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http:// creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.en_US
dc.subjectCloud coveren_US
dc.subjectMeteorologyen_US
dc.subjectPhotovoltaicsen_US
dc.subjectWeather predictionen_US
dc.titleCan photovoltaics be used to estimate cloud cover?en_US
dc.typeArticleen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryEnvironmental Engineeringen_US
dc.journalsOpen Accessen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1080/14786451.2020.1777129en_US
dc.identifier.scopus2-s2.0-85087038061en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85087038061en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.contributor.orcid#NODATA#en
dc.relation.issue9en_US
dc.relation.volume39en_US
cut.common.academicyear2019-2020en_US
dc.identifier.spage880en_US
dc.identifier.epage895en_US
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.languageiso639-1en-
crisitem.journal.journalissn1478-646X-
crisitem.journal.publisherTaylor & Francis-
crisitem.author.deptDepartment of Chemical Engineering-
crisitem.author.deptDepartment of Chemical Engineering-
crisitem.author.facultyFaculty of Geotechnical Sciences and Environmental Management-
crisitem.author.facultyFaculty of Geotechnical Sciences and Environmental Management-
crisitem.author.orcid0000-0002-4957-4772-
crisitem.author.orcid0000-0002-0374-2128-
crisitem.author.parentorgFaculty of Geotechnical Sciences and Environmental Management-
crisitem.author.parentorgFaculty of Geotechnical Sciences and Environmental Management-
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