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Temporary Variables for Predicting Electricity Consumption Through Data Mining

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, , Citation Jesús Silva et al 2020 J. Phys.: Conf. Ser. 1432 012033 DOI 10.1088/1742-6596/1432/1/012033

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This article is retracted by 2020 J. Phys.: Conf. Ser. 1432 012100

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jesussilvaUPC@gmail.com

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1 Universidad Peruana de Ciencias Aplicadas, Lima, Perú

2 Universidad de la Costa, Barranquilla, Atlántico, Colombia

3 Universidad del Atlántico, Puerto Colombia, Atlántico, Colombia.

4 Universidad del Sucre, Sincelejo, Sucre, Colombia.

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1742-6596/1432/1/012033

Abstract

In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids allows real-time collection of data on the operating status of the electricity grid. Based on this availability of data, it is feasible and convenient to predict consumption in the short term, from a few hours to a week. The hypothesis of the study is that the method used to present time variables to a prediction system of electricity consumption affects the results.

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This paper was retracted by IOP Publishing on 15 Sep 2020.

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10.1088/1742-6596/1432/1/012033