PCSTCOL: Power consumption data from an area of southern Colombia

Published: 14 January 2020| Version 3 | DOI: 10.17632/xbt7scz5ny.3
Jorge Parraga-Alava


Herein, we introduce a dataset concerning electric-power consumption-related features registered in seven main municipalities of Nariño, Colombia, from December 2010 to May 2016. The dataset consists of 4427 socio-demographic characteristics, and 6 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.2



Corporacion Universitaria Autonoma de Narino, Universidad de Buenos Aires, Pontificia Universidad Javeriana, Universidad de Narino, Universidad Tecnica del Norte, Universidad Tecnica de Manabi


Electric Power, Machine Learning, Forecasting, Energy Forecasting, Smart Grid