Over the years, many countries have resorted to renewable energy sources (RESs), among which solar energy appears to be the most promising. Conse- quently, the photovoltaic technology (PV) is a steadily growing energy sector worldwide. However, the performance of PV systems depends heavily on the weather conditions. The chaotic nature of meteorological conditions hinders effective power management of any PV system. The scientific literature has ex- plored and continues to explore methods to predict the PV power production. This work investigates a Deep Learning (DL) approach for short-term forecast- ing of the solar radiation as Global Horizontal Irradiance (GHI), one of the most important parameters that affect the PV power production.