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Time series forecasting for Colombian mining and quarrying electricity demand

10.24050/reia.v18i35.1458
Published 2021-01-01
Articles

Abstract

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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Authors

  • Maria D. Mariño

    Universidad Pontificia Bolivariana

  • Adriana Arango

    Universidad Nacional de Colombia

  • Laura Lotero

    Universidad Pontificia Bolivariana

  • Maritza Jimenez

    Universidad Nacional de Colombia

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