Recent Advances in Energy Time Series Forecasting

Francisco Martínez-Álvarez, Alicia Troncoso and José C. Riquelme
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Francisco Martínez-Álvarez: Department of Computer Science, Pablo de Olavide University, ES-41013 Seville, Spain
Alicia Troncoso: Department of Computer Science, Pablo de Olavide University, ES-41013 Seville, Spain
José C. Riquelme: Department of Computer Science, University of Seville, 41012 Seville, Spain

Energies, 2017, vol. 10, issue 6, 1-3

Abstract: This editorial summarizes the performance of the special issue entitled Energy Time Series Forecasting, which was published in MDPI’s Energies journal. The special issue took place in 2016 and accepted a total of 21 papers from twelve different countries. Electrical, solar, or wind energy forecasting were the most analyzed topics, introducing brand new methods with very sound results.

Keywords: energy; time series; forecasting (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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