Prediction of the Daily Direct Solar Radiation Using Nonlinear Autoregressive Exogenous (NARX) Network Model
| dc.rights.license | open | en_US |
| dc.contributor.author | BOUSSAADA, Zina | |
| hal.structure.identifier | Laboratoire de l'intégration, du matériau au système [IMS] | |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | REMACI, Ahmed | |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | CUREA, Octavian
ORCID: 0000-0002-5030-2088 IDREF: 68259131 | |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | CAMBLONG, Haritza | |
| dc.contributor.author | BELLAAJ, Najiba | |
| dc.date.accessioned | 2023-10-16T07:15:39Z | |
| dc.date.available | 2023-10-16T07:15:39Z | |
| dc.date.conference | 2017-06-27 | |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/184406 | |
| dc.description.abstractEn | The work presented in this paper focuses on the estimation of the direct solar radiation on a horizontal surface using Nonlinear Autoregressive Exogenous (NARX) neural network model. This study is a part of a research project which consists in supplying a sailboat with electricity using only renewable sources. Therefore the results will be used to estimate the direct solar radiation on a tilted surface and the amount of available power from Photovoltaic in the sailboat. In this paper, the NARX neural network predicts the daily direct solar radiation using two variables: the determinist component of solar radiation and its statistical component. Due the mobility of the sailboat and the difference between the days of the year, the issue of this research is to find the best neural network to be used for the daily direct solar radiation prediction. Using several simulations, the best performance was obtained when the training phase was done periodically. | |
| dc.language.iso | EN | en_US |
| dc.subject.en | cloud cover | |
| dc.subject.en | Artificial Neural Network | |
| dc.subject.en | mathematic model | |
| dc.subject.en | Estimation | |
| dc.subject.en | statistical model | |
| dc.title.en | Prediction of the Daily Direct Solar Radiation Using Nonlinear Autoregressive Exogenous (NARX) Network Model | |
| dc.type | Communication dans un congrès | en_US |
| dc.subject.hal | Physique [physics] | en_US |
| bordeaux.hal.laboratories | ESTIA - Recherche | en_US |
| bordeaux.hal.laboratories | IMS : Laboratoire de l'Intégration du Matériau au Système - UMR 5218 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | Bordeaux INP | en_US |
| bordeaux.institution | Bordeaux Sciences Agro | en_US |
| bordeaux.conference.title | SEEP 2017 - 10th International Conference on Sustainable Energy and Environmental Protection | en_US |
| bordeaux.country | si | en_US |
| bordeaux.conference.city | Bled | en_US |
| bordeaux.import.source | hal | |
| hal.identifier | hal-01631169 | |
| hal.version | 1 | |
| hal.invited | non | en_US |
| hal.proceedings | non | en_US |
| hal.conference.end | 2017-06-30 | |
| hal.popular | non | en_US |
| hal.audience | Internationale | en_US |
| hal.export | false | |
| workflow.import.source | hal | |
| dc.rights.cc | Pas de Licence CC | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=BOUSSAADA,%20Zina&REMACI,%20Ahmed&CUREA,%20Octavian&CAMBLONG,%20Haritza&BELLAAJ,%20Najiba&rft.genre=unknown |
