Short-term Multi Horizons Forecasting of Solar Irradiation Based on Artificial Neural Network with Meteorological Data: Application in the North-west of Senegal
| Autor: | Francoise Grandvaux, Laurent Tabourot, Willy Magloire Nkounga, Mamadou Ndiaye, Mouhamadou Falilou Ndiaye, Momadou Bop, Oumar Ibn Khatab Cisse |
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| Přispěvatelé: | École Supérieure Polytechnique de Dakar (ESP), Université Cheikh Anta Diop [Dakar, Sénégal] (UCAD), Laboratoire SYstèmes et Matériaux pour la MEcatronique (SYMME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Université Paris Nanterre (UPN), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), CEA-MITIC, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Mean squared error
Correlation coefficient Meteorology Artificial neural network business.industry neural network Photovoltaic system forecasting solar irradiation Solar energy 7. Clean energy Term (time) [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] Levenberg–Marquardt algorithm multi horizons 13. Climate action Environmental science levenbergmarquardt business Solar power |
| Zdroj: | 2021 Sixteenth International Conference on Ecological Vehicles and Renewable Energies (EVER) 2021 Sixteenth International Conference on Ecological Vehicles and Renewable Energies (EVER), May 2021, Monte-Carlo, France. pp.1-8, ⟨10.1109/EVER52347.2021.9456600⟩ EVER |
| DOI: | 10.1109/EVER52347.2021.9456600⟩ |
| Popis: | International audience; This study proposes a short term forecasting of solar irradiation with multi horizons in the northwest of Senegal. The multilayer artificial neural network (ANN), based on the Levenberg Marquardt algorithm and the meteorological data are used. The latter are measured in real time on the study site. The variables of interest are: mean solar irradiation, maximum temperature and measurement time; they are selected using Weka software. The forecasting horizons are: 0.5 hour, 1 hour, 1.5 hours, 2 hours, 2.5 hours, 3 hours, 3.5 hours, 4 hours, 4.5 hours, 5 hours, 5.5 hours and 06 hours. They are proposed with the corresponding statistical criteria. The results show that, the solar energy forecasting can be extended over a six-hour horizon with a correlation coefficient of 0.97 and root mean square error of 0.07. These results will make it possible to complete the forecasting tools in the solar energy sector in Senegal, and help investors to choose the most suitable horizons for energy forecasting in photovoltaic solar power plants. |
| Databáze: | OpenAIRE |
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