New Model of Photovoltaic System Adapted by a Digital MPPT Control and Radiation Predictions Using Deep Learning

Authors

  • Amal Zouhri Sidi Mohamed Ben Abdellah University, Faculty of Sciences, Laboratory of Computer Science, Signals, Automatics and Cognitivism, Fez, Morocco
  • Mostafa El Mallahi Sidi Mohamed Ben Abdellah University,High Normal Scool Fez, Fez, Morocco
Keywords: Machine Learning, Deep Learning, Artificial Intelligence, Renewable Energies, Solar Radiation

Abstract

Forecasting solar radiation is one of the most useful impacts that can give us a deep vision on maintaining the integrity of solar systems. The availability and ease of use of the data make this process simpler. Predictions may be produced using various data sources. In fact, there are two different forms that can be identified. The first one was the use of historical solar radiation data, while the second one was the use of other meteorological parameters. The availability and choice of the data source can have an effect on the choice of the model and methods used. Our proposed article aims to take research as an example to review the solar radiation situation in Morocco and outline the methods of predicting solar radiation using different machine learning and deep learning methods like ANN, MLP, BPNN, DNN, and LSTM, which are used in different regions in Morocco.

Downloads

Published
22.01.2024
Issue
Section
Articles

How to Cite

Zouhri, A., & El Mallahi, M. (2024). New Model of Photovoltaic System Adapted by a Digital MPPT Control and Radiation Predictions Using Deep Learning. Journal of Automation, Mobile Robotics and Intelligent Systems, 17(2), 71-84. https://doi.org/10.14313/2-2023/17