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A data set for electric power consumption forecasting based on socio-demographic features: Data from an area of
Jorge Parraga-Alava1, Jorge Dario Moncayo-Nacaza2, Javier Revelo-Fuelagán3
1Facultad de Ciencias Informáticas, Universidad Técnica de Manabí, Portoviejo, Ecuador.
Abstract:
In this article, we introduce a data set concerning electric-power consumption-related features registered in seven main municipalities of Nariño, Colombia, from December 2010 to May 2016. The data set consists of 4427 socio-demographic characteristics, and 7 power-consumption-referred measured values. Data were fully collected by the company Centrales Eléctricas de Nariño (CEDENAR) according to the client consumption records. Power consumption data collection was carried following a manual procedure wherein company workers are in charge of manually registering the readings (measured in kWh) reported by the electric energy meters installed at each housing/building. Released data set is aimed at providing researchers a suitable input for designing and assessing the performance of forecasting, modelling, simulation and optimization approaches applied to electric power consumption prediction and characterization problems. The data set, so-named in shorthand PCSTCOL, is freely and publicly available at https://doi.org/10.17632/xbt7scz5ny.3.
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