@article{
 title = {A data set for electric power consumption forecasting based on socio-demographic features: Data from an area of southern Colombia},
 type = {article},
 year = {2020},
 keywords = {Electric power consumption,Forecasting,Machine learning,Smart grid,Socio-demographic data},
 websites = {https://www.sciencedirect.com/science/article/pii/S2352340920301402},
 id = {5870a7ea-adc1-3e96-9f37-b16dab7c64e5},
 created = {2020-12-29T22:52:14.175Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 last_modified = {2021-02-20T22:05:34.291Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Parraga-Alava2020},
 private_publication = {false},
 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.},
 bibtype = {article},
 author = {Parraga-Alava, Jorge and Moncayo-Nacaza, Jorge Dario and Revelo-Fuelagán, Javier and Rosero-Montalvo, Paul D. and Anaya-Isaza, Andrés and Peluffo-Ordóñez, Diego Hernán},
 doi = {10.1016/j.dib.2020.105246},
 journal = {Data in Brief}
}

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