Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area
Nowadays, it is of great interest to know and forecast the solar energy resource that will be constantly available in order to optimize its use. The generation of electrical energy using CSP (concentrated solar power) plants is mostly affected by atmospheric changes. Therefore, forecasting solar irr...
| Main Authors: | , , , , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
| Published: |
MDPI
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/8001 |
| _version_ | 1789406755116023808 |
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| author | Mondragón, Román Alonso Montesinos, Joaquín Blas Riveros Rosas, David Valdés, Mauro Estévez, Héctor González Cabrera, Adriana E. Stremme, Wolfgang |
| author_facet | Mondragón, Román Alonso Montesinos, Joaquín Blas Riveros Rosas, David Valdés, Mauro Estévez, Héctor González Cabrera, Adriana E. Stremme, Wolfgang |
| author_sort | Mondragón, Román |
| collection | DSpace |
| description | Nowadays, it is of great interest to know and forecast the solar energy resource that will be constantly available in order to optimize its use. The generation of electrical energy using CSP (concentrated solar power) plants is mostly affected by atmospheric changes. Therefore, forecasting solar irradiance is essential for planning a plant’s operation. Solar irradiance/atmospheric (clouds) interaction studies using satellite and sky images can help to prepare plant operators for solar surface irradiance fluctuations. In this work, we present three methodologies that allow us to estimate direct normal irradiance (DNI). The study was carried out at the Solar Irradiance Observatory (SIO) at the Geophysics Institute (UNAM) in Mexico City using corresponding images obtained with a sky camera and starting from a clear sky model. The multiple linear regression and polynomial regression models as well as the neural networks model designed in the present study, were structured to work under all sky conditions (cloudy, partly cloudy and cloudless), obtaining estimation results with 82% certainty for all sky types. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-8001 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-80012023-04-12T19:48:36Z Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area Mondragón, Román Alonso Montesinos, Joaquín Blas Riveros Rosas, David Valdés, Mauro Estévez, Héctor González Cabrera, Adriana E. Stremme, Wolfgang cloud detection digitized image processing artificial neural networks solar irradiance estimation solar irradiance forecasting solar energy sky camera remote sensing CSP plants Nowadays, it is of great interest to know and forecast the solar energy resource that will be constantly available in order to optimize its use. The generation of electrical energy using CSP (concentrated solar power) plants is mostly affected by atmospheric changes. Therefore, forecasting solar irradiance is essential for planning a plant’s operation. Solar irradiance/atmospheric (clouds) interaction studies using satellite and sky images can help to prepare plant operators for solar surface irradiance fluctuations. In this work, we present three methodologies that allow us to estimate direct normal irradiance (DNI). The study was carried out at the Solar Irradiance Observatory (SIO) at the Geophysics Institute (UNAM) in Mexico City using corresponding images obtained with a sky camera and starting from a clear sky model. The multiple linear regression and polynomial regression models as well as the neural networks model designed in the present study, were structured to work under all sky conditions (cloudy, partly cloudy and cloudless), obtaining estimation results with 82% certainty for all sky types. 2020-04-13T11:18:24Z 2020-04-13T11:18:24Z 2020-04-09 info:eu-repo/semantics/article 2072-4292 http://hdl.handle.net/10835/8001 en https://www.mdpi.com/2072-4292/12/7/1212 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | cloud detection digitized image processing artificial neural networks solar irradiance estimation solar irradiance forecasting solar energy sky camera remote sensing CSP plants Mondragón, Román Alonso Montesinos, Joaquín Blas Riveros Rosas, David Valdés, Mauro Estévez, Héctor González Cabrera, Adriana E. Stremme, Wolfgang Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area |
| title | Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area |
| title_full | Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area |
| title_fullStr | Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area |
| title_full_unstemmed | Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area |
| title_short | Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area |
| title_sort | attenuation factor estimation of direct normal irradiance combining sky camera images and mathematical models in an inter-tropical area |
| topic | cloud detection digitized image processing artificial neural networks solar irradiance estimation solar irradiance forecasting solar energy sky camera remote sensing CSP plants |
| url | http://hdl.handle.net/10835/8001 |
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