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dc.contributor.author
Sánchez Reinoso, Carlos Roberto
dc.contributor.author
Cutrera, M.
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Battioni, M.
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Milone, Diego Humberto
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Buitrago, R. H.
dc.date.available
2023-05-04T18:06:41Z
dc.date.issued
2012-10
dc.identifier.citation
Sánchez Reinoso, Carlos Roberto; Cutrera, M.; Battioni, M.; Milone, Diego Humberto; Buitrago, R. H.; Photovoltaic generation model as a function of weather variables using artificial intelligence techniques; Pergamon-Elsevier Science Ltd; International Journal of Hydrogen Energy; 37; 19; 10-2012; 14781-14785
dc.identifier.issn
0360-3199
dc.identifier.uri
http://hdl.handle.net/11336/196334
dc.description.abstract
The optimisation of photovoltaic systems of electricity generation involve the necesity of real data of the different variables as well as determination of their relationships. In the field of photovoltaic solar energy there is interest to predict the energy generation in terms of solar radiation and climatic parameters. For this purpose, it is needed a good sensing and measurement of these parameters. In this paper, we propose a method based on artificial intelligence techniques for obtaining the generated energy under climatic conditions during a year. In addition, we propose a model that relates short-circuit current with radiation, considering the true nonlinear behavior of the relationship between variables. The results of the proposed method using real data show its validity and usefulness in predicting the generated energy by photovoltaic modules and the search for alternative methods of measuring global radiation at low cost and reasonable error.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ARTIFICIAL INTELLIGENCE
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GENERATION PREDICTION
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MEASUREMENTS
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PHOTOVOLTAIC ENERGY
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Otras Ciencias de la Computación e Información
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Ciencias de la Computación e Información
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CIENCIAS NATURALES Y EXACTAS
dc.title
Photovoltaic generation model as a function of weather variables using artificial intelligence techniques
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-03-23T12:39:10Z
dc.journal.volume
37
dc.journal.number
19
dc.journal.pagination
14781-14785
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Sánchez Reinoso, Carlos Roberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina
dc.description.fil
Fil: Cutrera, M.. Universidad Nacional de Catamarca; Argentina
dc.description.fil
Fil: Battioni, M.. Universidad Nacional de Catamarca; Argentina
dc.description.fil
Fil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina
dc.description.fil
Fil: Buitrago, R. H.. Universidad Nacional de Catamarca; Argentina
dc.journal.title
International Journal of Hydrogen Energy
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0360319911027741
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.ijhydene.2011.12.081
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