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An econometric analysis of electricity demand response to price changes at the intra-day horizon: The case of manufacturing industry in West Denmark

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  • Møller, Niels Framroze
  • Møller Andersen, Frits

Abstract

The use of renewable energy implies a more variable supply of power. Market efficiency may improve if demand can absorb some of this variability by being more flexible, e.g. by responding quickly to changes in the market price of power. To learn about this, in particular, whether demand responds already within the same day, we suggest an econometric model for hourly consumption and price time series. This allows for multi-level seasonality and that information about day-ahead prices does not arrive every hour but every 24th hour (as a vector of 24 prices). We confront the model with data from the manufacturing industry of West Denmark (2007-2011). The results clearly suggest a lack of response. The policy implication is that relying exclusively on hourly price response by consumers for integrating volatile renewable electricity production is questionable. Either hourly price variation has to increase considerably or demand response technologies be installed.

Suggested Citation

  • Møller, Niels Framroze & Møller Andersen, Frits, 2015. "An econometric analysis of electricity demand response to price changes at the intra-day horizon: The case of manufacturing industry in West Denmark," MPRA Paper 66178, University Library of Munich, Germany, revised 15 Aug 2015.
    • Handle: RePEc:pra:mprapa:66178
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    References listed on IDEAS

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    Cited by:

    1. Andersen, Frits Møller & Baldini, Mattia & Hansen, Lars Gårn & Jensen, Carsten Lynge, 2017. "Households’ hourly electricity consumption and peak demand in Denmark," Applied Energy, Elsevier, vol. 208(C), pages 607-619.
    2. Hirth, Lion & Khanna, Tarun M. & Ruhnau, Oliver, 2024. "How aggregate electricity demand responds to hourly wholesale price fluctuations," Energy Economics, Elsevier, vol. 135(C).

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    More about this item

    Keywords

    Demand Response; Electricity Demand; Day-ahead prices; Econometrics; RegARIMA;
    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
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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