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Revista EIA
Print version ISSN 1794-1237On-line version ISSN 2463-0950
Abstract
MARINO, MARÍA DÁMELA; ARANGO, ADRIANA; LOTERO, LAURA and JIMENEZ, MARITZA. Time series forecasting for Colombian mining and quarrying electricity demand. Rev.EIA.Esc.Ing.Antioq [online]. 2021, vol.18, n.35, pp.77-99. Epub Oct 26, 2021. ISSN 1794-1237. https://doi.org/10.24050/reia.v18i35.1458.
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.
Keywords : time series; forecasting models; electricity demand; mining and quarrying; holt winters; SARIMA; additive model; Colombia; planning; strategy.