Abstract
This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal. The special issue took place in 2017 and accepted a total of 13 papers from 7 different countries. Electrical, solar and wind energy forecasting were the most analyzed topics, introducing new methods with applications of utmost relevance.
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Martínez-Álvarez, F., Troncoso, A., & Riquelme, J. C. (2018). Data science and big data in energy forecasting. Energies, 11(11). https://doi.org/10.3390/en11113224
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