Machine Learning for Solar Radiation Estimation

Dear Colleagues,

The interest in solar radiation prediction has increased greatly in recent times as a direct consequence of the exponential grow in the use of renewable energies. In this regard, a large number of different techniques have been developed to predict solar (global, direct, and/or diffuse) radiation: empirical models, numerical weather models, satellite-based schemes, etc. Among all of them, machine learning techniques have proven their capacities as a reliable and cost-efficient alternative to the more traditional approaches, showing their high capacity for obtaining robust results in solar radiation estimation problems using different sets of input variables.
This Special Issue deals with machine learning methods in solar radiation prediction, at any time horizon and in any part of the world. Articles discussing novel machine learning-based predictive approaches, original works using innovative input data as predictive variables, new algorithms or revisited algorithms providing good solutions to difficult problems in solar radiation estimation are welcome.

Dr. Carlos Casanova-Mateo
Guest Editor

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