Abstract
This paper proposes a model for the daily electricity demand in Uruguay, identifying the incidence of special days (calendar effects, holidays, among others) and climatic variables such as temperature, humidity, winds, and heliophany. We propose a non-linear model to represent the association between energy consumption and climate variables. Applying Markov switching models and considering hot and cold months separately, identify breaks in the energy demand function associated with temperature thresholds. Predictive analysis during 2020, the first year of the health emergency, shows that the COVID-19 sanitary crisis did not deteriorate the model performance.
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Notes
- 1.
These results and full estimations are available on request from the authors.
- 2.
The individual incidence was estimated in a broader sample (1992–2018).
- 3.
The estimated coefficients in Eq. (7), for each group of special holidays, are available as Complementary Material.
- 4.
Full estimates are available on request from the authors.
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Lanzilotta, B., Rodríguez-Collazo, S. (2023). Forecasting High-Frequency Electricity Demand in Uruguay. In: Valenzuela, O., Rojas, F., Herrera, L.J., Pomares, H., Rojas, I. (eds) Theory and Applications of Time Series Analysis and Forecasting. ITISE 2021. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-031-14197-3_15
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