Corrigendum to “Forecasting electricity demand of municipalities through artificial neural networks and metered supply point classification”, [vol. 11, June 2024, 3533–3549] (Energy Reports (2024) 11 (3533–3549), (S2352484724001689), (10.1016/j.egyr.2024.03.023))
S. Mateo-Barcos (Universitat Politécnica de Valencia)
D.G. Ribo-Perez (TU Delft - Energy and Industry, Universitat Politécnica de Valencia)
J. Rodriguez-Garcia (Universitat Politécnica de Valencia)
M. Alcázar-Ortega (Universitat Politécnica de Valencia)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
The authors regret <To not have included during the publication process the acknowledgement to a project that has been part of this work and want to include in the acknowledgements part: This work was partially supported by the Grant TED2021-129722B-C31 (ALIVE-DER), funded by MCIN/AEI/10.13039/501100011033 and by “European Union NextGenerationEU/PRTR”. >. The authors would like to apologise for any inconvenience caused.
help_outline