Time series forecasting for Colombian mining and quarrying electricity demand

Modelos de series temporales para pronóstico de la demanda eléctrica del sector de explotación de minas y canteras en Colombia

Published 2021-01-01

Modelos de series temporales
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Vol. 18 No. 35 (2021)
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Time series forecasting for Colombian mining and quarrying electricity demand. (2021). Revista EIA, 18(35), 35007 pp. 1-23. https://doi.org/10.24050/reia.v18i35.1458
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https://doi.org/10.24050/reia.v18i35.1458
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Maria D. Mariño
Universidad Pontificia Bolivariana
Adriana Arango
Universidad Pontificia Bolivariana, Universidad Nacional de Colombia
Laura Lotero
Universidad Pontificia Bolivariana
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Maritza Jimenez
Universidad Pontificia Bolivariana, Universidad Nacional de Colombia
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Demand forecasting is of utmost importance for strategic decision making of a nation. Literature offers multiple approaches to the development of forecast models focused in aggregate demand, also, little attention has been paid to non-residential sector demand forecasts. In this paper, using Time Series Analysis approach, three different models are fitted, tested and compared to forecast electricity demand in mining and quarrying sector, one of the most representative non-residential sector for colombian electricity demand. Fitted models include an additive model, a SARIMA and a Holt Winters model. Results indicate that better accuracy is provided the by Holt Winters model.

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