A data set for electric power consumption forecasting based on socio-demographic features: Data from an area of southern Colombia

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 valu...

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Bibliographic Details
Published in:Data in brief 2020-04, Vol.29, p.105246-105246, Article 105246
Main Authors: Parraga-Alava, Jorge, Moncayo-Nacaza, Jorge Dario, Revelo-Fuelagán, Javier, Rosero-Montalvo, Paul D., Anaya-Isaza, Andrés, Peluffo-Ordóñez, Diego Hernán
Format: Article
Language:English
Subjects:
Computer Science
Electric power consumption
Forecasting
Machine learning
Smart grid
Socio-demographic data
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Summary: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.
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2020.105246