Abstract
With the increased number of solar power plants, the variation in solar resources causes many problems with grid management and energy systems in general. This is why artificial intelligence (AI) technologies have become useful. AI abilities have been set to use in a variety of situations to handle difficult challenges. The forecast of solar radiation using AI approaches provides a good picture of the integrity of the solar system. This process is simplified by the availability and easy use of different data sources. In reality, there are two famous methods for solar radiation predictions. The first was to use historical solar data, while the second was to integrate other weather parameters. This paper describes the solutions to solar systems and grid management issues using artificial intelligence approaches. It also outlines algorithms for solar radiation prediction by various Machine Learning and Deep Learning techniques, such as ANN, MLP, BPNN, DNN, and LSTM, utilized in various Morocco regions.
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Boutahir, M.K., Farhaoui, Y., Azrour, M. (2022). Machine Learning and Deep Learning Applications for Solar Radiation Predictions Review: Morocco as a Case of Study. In: Yaseen, S.G. (eds) Digital Economy, Business Analytics, and Big Data Analytics Applications. Studies in Computational Intelligence, vol 1010. Springer, Cham. https://doi.org/10.1007/978-3-031-05258-3_6
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