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Comparative Analysis of Methods for Hourly Electricity Demand Forecasting in the Absence of Data – A Case Study

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  • Zawadzki Jan

    (1 Faculty of Economics, Department of Applications of Mathematics in Economics Professor emeritus, West Pomeranian University of Technology in Szczecin, Poland)

Abstract

This paper examines the impact of the number of gaps in data, the analytical form, and the model type selection criterion on the accuracy of interpolation and extrapolation forecasts for hourly data.

Suggested Citation

  • Zawadzki Jan, 2023. "Comparative Analysis of Methods for Hourly Electricity Demand Forecasting in the Absence of Data – A Case Study," Economic and Regional Studies / Studia Ekonomiczne i Regionalne, Sciendo, vol. 16(1), pages 34-50, March.
    • Handle: RePEc:vrs:ecoreg:v:16:y:2023:i:1:p:34-50:n:8
    DOI: 10.2478/ers-2023-0003
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    References listed on IDEAS

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    1. Dordonnat, V. & Koopman, S.J. & Ooms, M. & Dessertaine, A. & Collet, J., 2008. "An hourly periodic state space model for modelling French national electricity load," International Journal of Forecasting, Elsevier, vol. 24(4), pages 566-587.
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    More about this item

    Keywords

    forecasting; missing data; time series; high frequency;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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