Machine learning can be applied on a wide variety of purposes, due to the ability of this technology to improve products and autonomy. The use of machine learning in solar technology is however not common, but has proven to be very valuable.
One of the applications of these tools is to predict how much solar energy can be captured at a specific location, in order for the solar product to function optimally. In this way, the product can be configured and optimized according to the needs of each client. Predicting the amount of generated solar energy is not easy, since solar irradiation varies a lot all over the globe and is subjected to local climates. These effects can be analysed and products can be optimised accordingly, by making use of dedicated machine learning algorithms.
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