Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks
Descripción del Articulo
ACKNOWLEDGMENT Franklin Alfredo Cabezas Huerta would like to thank the support provided by the CER – UNI and also express special thanks to the National Fund for Scientific and Technological Development (FONDECYT – PERU) for the scholarship awarded to do PhD studies in Science with mention in Energe...
| Autores: | , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2019 |
| Institución: | Consejo Nacional de Ciencia Tecnología e Innovación |
| Repositorio: | CONCYTEC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.concytec.gob.pe:20.500.12390/2297 |
| Enlace del recurso: | https://hdl.handle.net/20.500.12390/2297 https://doi.org/10.1109/SHIRCON48091.2019.9024856 |
| Nivel de acceso: | acceso abierto |
| Materia: | solar radiation Artificial Neural Networks astronomical equations estimated values Solar energy systems http://purl.org/pe-repo/ocde/ford#2.02.04 |
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| dc.title.none.fl_str_mv |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks |
| title |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks |
| spellingShingle |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks Huerta F.A.C. solar radiation Artificial Neural Networks astronomical equations estimated values Solar energy systems http://purl.org/pe-repo/ocde/ford#2.02.04 |
| title_short |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks |
| title_full |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks |
| title_fullStr |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks |
| title_full_unstemmed |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks |
| title_sort |
Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks |
| author |
Huerta F.A.C. |
| author_facet |
Huerta F.A.C. Soldevilla F.R.C. Delgado A. Carbajal C. |
| author_role |
author |
| author2 |
Soldevilla F.R.C. Delgado A. Carbajal C. |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Huerta F.A.C. Soldevilla F.R.C. Delgado A. Carbajal C. |
| dc.subject.none.fl_str_mv |
solar radiation |
| topic |
solar radiation Artificial Neural Networks astronomical equations estimated values Solar energy systems http://purl.org/pe-repo/ocde/ford#2.02.04 |
| dc.subject.es_PE.fl_str_mv |
Artificial Neural Networks astronomical equations estimated values Solar energy systems |
| dc.subject.ocde.none.fl_str_mv |
http://purl.org/pe-repo/ocde/ford#2.02.04 |
| description |
ACKNOWLEDGMENT Franklin Alfredo Cabezas Huerta would like to thank the support provided by the CER – UNI and also express special thanks to the National Fund for Scientific and Technological Development (FONDECYT – PERU) for the scholarship awarded to do PhD studies in Science with mention in Energetics in the National University of Engineering. |
| publishDate |
2019 |
| dc.date.accessioned.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.available.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.issued.fl_str_mv |
2019 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12390/2297 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1109/SHIRCON48091.2019.9024856 |
| dc.identifier.scopus.none.fl_str_mv |
2-s2.0-85082388289 |
| url |
https://hdl.handle.net/20.500.12390/2297 https://doi.org/10.1109/SHIRCON48091.2019.9024856 |
| identifier_str_mv |
2-s2.0-85082388289 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartof.none.fl_str_mv |
SHIRCON 2019 - 2019 IEEE Sciences and Humanities International Research Conference |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
| publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
| dc.source.none.fl_str_mv |
reponame:CONCYTEC-Institucional instname:Consejo Nacional de Ciencia Tecnología e Innovación instacron:CONCYTEC |
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Consejo Nacional de Ciencia Tecnología e Innovación |
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CONCYTEC |
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CONCYTEC |
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CONCYTEC-Institucional |
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CONCYTEC-Institucional |
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Repositorio Institucional CONCYTEC |
| repository.mail.fl_str_mv |
repositorio@concytec.gob.pe |
| _version_ |
1839175618768404480 |
| spelling |
Publicationrp05437600rp05438600rp05436600rp05435600Huerta F.A.C.Soldevilla F.R.C.Delgado A.Carbajal C.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2019https://hdl.handle.net/20.500.12390/2297https://doi.org/10.1109/SHIRCON48091.2019.90248562-s2.0-85082388289ACKNOWLEDGMENT Franklin Alfredo Cabezas Huerta would like to thank the support provided by the CER – UNI and also express special thanks to the National Fund for Scientific and Technological Development (FONDECYT – PERU) for the scholarship awarded to do PhD studies in Science with mention in Energetics in the National University of Engineering.Solar energy systems use solar radiation to obtain useful energy, so to design and implement these systems anywhere on the surface of the earth it is very important to know the value of the incident solar radiation in the selected place. This radiation is usually obtained from meters such as pyranometers, pyrheliometers or actinographs from meteorological stations located near the place. As these instruments are expensive and usually have high measurement errors (5-9%), it is necessary to estimate the radiation in an optimal way. In this work, two mathematical methods are used to estimate the value of incident solar radiation on horizontal and tilted surfaces. The methods are: Method based on astronomical equations and method based on Artificial Neural Networks. The case study was conducted for the geographical location of the National University of Engineering (Lima, Peru). A database of meteorological variables measured for ten years and averaged every month was used to compare their measurements with the estimated results of the proposed mathematical methods. The results revealed that the estimated values of global solar radiation when applying the astronomical method differs on average 9% with respect to that provided by the database and 6% when applying Artificial Neural Networks. © 2019 IEEE.Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - ConcytecengInstitute of Electrical and Electronics Engineers Inc.SHIRCON 2019 - 2019 IEEE Sciences and Humanities International Research Conferenceinfo:eu-repo/semantics/openAccesssolar radiationArtificial Neural Networks-1astronomical equations-1estimated values-1Solar energy systems-1http://purl.org/pe-repo/ocde/ford#2.02.04-1Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networksinfo:eu-repo/semantics/articlereponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC20.500.12390/2297oai:repositorio.concytec.gob.pe:20.500.12390/22972024-05-30 16:06:59.029http://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="7ec41e4a-2981-41c9-b447-4fdf99e69fd6"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Optimal Estimation of Solar Radiation on Flat Surfaces for the Design of Energy Systems using Artificial Neural Networks</Title> <PublishedIn> <Publication> <Title>SHIRCON 2019 - 2019 IEEE Sciences and Humanities International Research Conference</Title> </Publication> </PublishedIn> <PublicationDate>2019</PublicationDate> <DOI>https://doi.org/10.1109/SHIRCON48091.2019.9024856</DOI> <SCP-Number>2-s2.0-85082388289</SCP-Number> <Authors> <Author> <DisplayName>Huerta F.A.C.</DisplayName> <Person id="rp05437" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Soldevilla F.R.C.</DisplayName> <Person id="rp05438" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Delgado A.</DisplayName> <Person id="rp05436" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Carbajal C.</DisplayName> <Person id="rp05435" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Institute of Electrical and Electronics Engineers Inc.</DisplayName> <OrgUnit /> </Publisher> </Publishers> <Keyword>solar radiation</Keyword> <Keyword>Artificial Neural Networks</Keyword> <Keyword>astronomical equations</Keyword> <Keyword>estimated values</Keyword> <Keyword>Solar energy systems</Keyword> <Abstract>Solar energy systems use solar radiation to obtain useful energy, so to design and implement these systems anywhere on the surface of the earth it is very important to know the value of the incident solar radiation in the selected place. This radiation is usually obtained from meters such as pyranometers, pyrheliometers or actinographs from meteorological stations located near the place. As these instruments are expensive and usually have high measurement errors (5-9%), it is necessary to estimate the radiation in an optimal way. In this work, two mathematical methods are used to estimate the value of incident solar radiation on horizontal and tilted surfaces. The methods are: Method based on astronomical equations and method based on Artificial Neural Networks. The case study was conducted for the geographical location of the National University of Engineering (Lima, Peru). A database of meteorological variables measured for ten years and averaged every month was used to compare their measurements with the estimated results of the proposed mathematical methods. The results revealed that the estimated values of global solar radiation when applying the astronomical method differs on average 9% with respect to that provided by the database and 6% when applying Artificial Neural Networks. © 2019 IEEE.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1 |
| score |
13.461011 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
