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Forecasting the Colombian Electricity Spot Price under a Functional Approach

Author

Listed:
  • Santiago Gall n

    (Departamento de Matem ticas y Estad stica, Facultad de Ciencias Econ micas, Universidad de Antioquia, Medell n, Colombia)

  • Jorge Barrientos

    (Departamento de Econom a, Facultad de Ciencias Econ micas, Universidad de Antioquia, Medell n, Colombia.)

Abstract

Forecasting the hourly electricity spot price plays a crucial role for agents involved in energy day-ahead markets. However, traditional time series processes used for this issue model each hour separately not taking into account the intraday energy market microstructure information. In this paper, we appeal to a Functional Data Analysis (FDA) viewpoint that allows modeling and forecasting the intraday electricity spot price of the Colombian Electricity Market. Specifically, we use the Hyndman-Ullah-Shang method, which relies on a functional principal component decomposition of the nonparametric smoothed price curves, where the short-term forecasts are obtained by using the empirical functional principal components and the univariate time series forecasts of the corresponding estimated scores. Results show that one of the main advantages of this approach is that it allows to capture the underlying intraday common structural patterns shared by the daily spot price curves, and also behaves well for one-month-ahead price predictions compared with standard benchmarks.

Suggested Citation

  • Santiago Gall n & Jorge Barrientos, 2021. "Forecasting the Colombian Electricity Spot Price under a Functional Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 67-74.
    • Handle: RePEc:eco:journ2:2021-02-9
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    References listed on IDEAS

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    Cited by:

    1. Jorge Barrientos Marin & Laura Marquez Marulanda & Fernando Villada Duque, 2023. "Analyzing Electricity Demand in Colombia: A Functional Time Series Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 75-84, January.

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    More about this item

    Keywords

    Day-ahead electricity price forecasting; Functional data analysis; Functional principal components; Functional time series forecasting.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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