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Open AccessEditorial
Energies 2017, 10(6), 809; doi:10.3390/en10060809

Recent Advances in Energy Time Series Forecasting

1
Department of Computer Science, Pablo de Olavide University, ES-41013 Seville, Spain
2
Department of Computer Science, University of Seville, 41012 Seville, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Enrico Sciubba
Received: 8 June 2017 / Revised: 12 June 2017 / Accepted: 12 June 2017 / Published: 14 June 2017
(This article belongs to the Special Issue Energy Time Series Forecasting)
View Full-Text   |   Download PDF [131 KB, uploaded 14 June 2017]

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. View Full-Text
Keywords: energy; time series; forecasting energy; time series; forecasting
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Martínez-Álvarez, F.; Troncoso, A.; Riquelme, J.C. Recent Advances in Energy Time Series Forecasting. Energies 2017, 10, 809.

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