Application of artificial neuronal networks for the prediction of monthly photovoltaic power using tilt angle as input in Rabat city, Morocco-Reference-Cited by-同舟云学术

Application of artificial neuronal networks for the prediction of monthly photovoltaic power using tilt angle as input in Rabat city, Morocco

Published:2024-06-26 Issue:1 Volume:45 Page:
ISSN:0143-0750
Container-title:International Journal of Ambient Energy
language:en
Short-container-title:International Journal of Ambient Energy

Author:

Riad Salma¹,Bekkioui Naoual¹,Simo-Tagne Merlin²,Macmanus Chinenye Ndukwu³^ORCID,Lamrani Bilal⁴,Ez-Zahraouy Hamid¹

Affiliation:

1. Laboratoire de Matière Condensée et Sciences Interdisciplinaires “Labellisée Research Unit CNRST” URL-CNRST-17, Faculty of Sciences, Mohammed V University in Rabat, Rabat, Morocco

2. INRAE, LERMAB, ERBE—F, University of Lorraine, Epinal, France

3. Department of Agricultural and Bio-resources Engineering, Michael Okpara University of Agriculture, Umuahia, Abia State, Nigeria

4. MANAPSE laboratory, Faculty of Sciences, Mohammed V University, Rabat, Morocco

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01430750.2024.2365809

Reference38 articles.

1. Trends and gaps in photovoltaic power forecasting with machine learning

2. Short-term solar radiation forecasting using a new seasonal clustering technique and artificial neural network

3. Estimating the power generating of a stand-alone solar photovoltaic panel using artificial neural networks and statistical methods.

4. Estimation of the maximum power and normal operating power of a photovoltaic module by neural networks

5. Artificial neural network decision support tool for assessment of the energy performance and the refurbishment actions for the non-residential building stock in Southern Italy

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