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Impacts of day-ahead versus real-time market prices on wholesale electricity demand in Texas

Author

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  • Damien, Paul
  • Fuentes-García, Ruth
  • Mena, Ramsés H.
  • Zarnikau, Jay

Abstract

The somewhat recent nodal market structure in Texas impacts wholesale day-ahead market (DAM) and real-time market (RTM) prices. However, comparative insights on consumer responses to both these prices have not received attention. This paper attempts to fill this void by developing a system-wide demand response model to better understand price elasticities under DAM and RTM pricing. These insights may also assist grid operators to develop improved short-term forecasts of electricity demand. Using a large dataset from the Electric Reliability Council of Texas and a hierarchical Bayesian population model, we offer new insights on how DAM and RTM pricing shapes demand for electricity, and the related consequences for maintaining a reliable electricity market.

Suggested Citation

  • Damien, Paul & Fuentes-García, Ruth & Mena, Ramsés H. & Zarnikau, Jay, 2019. "Impacts of day-ahead versus real-time market prices on wholesale electricity demand in Texas," Energy Economics, Elsevier, vol. 81(C), pages 259-272.
    • Handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:259-272
    DOI: 10.1016/j.eneco.2019.04.008
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    References listed on IDEAS

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    Cited by:

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    2. Silvana Tiedemann & Raffaele Sgarlato & Lion Hirth, 2023. "Price elasticity of electricity demand: Using instrumental variable regressions to address endogeneity and autocorrelation of high-frequency time series," Papers 2306.12863, arXiv.org.
    3. John Robertson & University of Dundee, Dundee, UK, 2020. "Volatility Transmission between Oil Prices and Stock Prices as a New Source of Instability: Lessons from the UK Experience," Asian Journal of Economics and Empirical Research, Asian Online Journal Publishing Group, vol. 7(2), pages 217-223.
    4. Clastres, Cédric & Khalfallah, Haikel, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Energy Economics, Elsevier, vol. 98(C).
    5. Cédric Clastres & Haikel Khalfallah, 2020. "Retailers' strategies facing demand response and markets interactions," Working Papers hal-03167543, HAL.
    6. Bejan, Ioana & Jensen, Carsten Lynge & Andersen, Laura M. & Hansen, Lars Gårn, 2021. "Inducing flexibility of household electricity demand: The overlooked costs of reacting to dynamic incentives," Applied Energy, Elsevier, vol. 284(C).

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    More about this item

    Keywords

    Electricity demand; Energy forecast; Price effects; Bayesian inference;
    All these keywords.

    JEL classification:

    • 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
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • L97 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Utilities: General
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation

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