IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v81y2019icp259-272.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988319301148
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2019.04.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hopper, Nicole & Goldman, Charles & Bharvirkar, Ranjit & Neenan, Bernie, 2006. "Customer response to day-ahead market hourly pricing: Choices and performance," Utilities Policy, Elsevier, vol. 14(2), pages 126-134, June.
    2. Robert H. Patrick & Frank A. Wolak, 2001. "Estimating the Customer-Level Demand for Electricity Under Real-Time Market Prices," NBER Working Papers 8213, National Bureau of Economic Research, Inc.
    3. Fan, Shu & Hyndman, Rob J., 2011. "The price elasticity of electricity demand in South Australia," Energy Policy, Elsevier, vol. 39(6), pages 3709-3719, June.
    4. J. Zarnikau & C. Woo & R. Baldick, 2014. "Did the introduction of a nodal market structure impact wholesale electricity prices in the Texas (ERCOT) market?," Journal of Regulatory Economics, Springer, vol. 45(2), pages 194-208, April.
    5. Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9780521671736, June.
    6. Woo, C.K. & Ho, T. & Zarnikau, J. & Olson, A. & Jones, R. & Chait, M. & Horowitz, I. & Wang, J., 2014. "Electricity-market price and nuclear power plant shutdown: Evidence from California," Energy Policy, Elsevier, vol. 73(C), pages 234-244.
    7. Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108437493, September.
    8. Tsai, Chen-Hao & Eryilmaz, Derya, 2018. "Effect of wind generation on ERCOT nodal prices," Energy Economics, Elsevier, vol. 76(C), pages 21-33.
    9. Woo, C.K. & Chen, Y. & Zarnikau, J. & Olson, A. & Moore, J. & Ho, T., 2018. "Carbon trading’s impact on California’s real-time electricity market prices," Energy, Elsevier, vol. 159(C), pages 579-587.
    10. Wai Choi & Anindya Sen & Adam White, 2011. "Response of industrial customers to hourly pricing in Ontario’s deregulated electricity market," Journal of Regulatory Economics, Springer, vol. 40(3), pages 303-323, December.
    11. Chi-Keung Woo, Ira Horowitz, Brian Horii, Ren Orans, and Jay Zarnikau, 2012. "Blowing in the Wind: Vanishing Payoffs of a Tolling Agreement for Natural-gas-fired Generation of Electricity in Texas," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    12. Woo, C.K. & Zarnikau, J. & Moore, J. & Horowitz, I., 2011. "Wind generation and zonal-market price divergence: Evidence from Texas," Energy Policy, Elsevier, vol. 39(7), pages 3928-3938, July.
    13. Lijesen, Mark G., 2007. "The real-time price elasticity of electricity," Energy Economics, Elsevier, vol. 29(2), pages 249-258, March.
    14. Zarnikau, J. & Woo, C.K. & Zhu, S. & Tsai, C.H., 2019. "Market price behavior of wholesale electricity products: Texas," Energy Policy, Elsevier, vol. 125(C), pages 418-428.
    15. Park, Haesun & Mjelde, James W. & Bessler, David A., 2006. "Price dynamics among U.S. electricity spot markets," Energy Economics, Elsevier, vol. 28(1), pages 81-101, January.
    16. Chan,Joshua & Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2019. "Bayesian Econometric Methods," Cambridge Books, Cambridge University Press, number 9781108423380, September.
    17. Redl, Christian & Haas, Reinhard & Huber, Claus & Böhm, Bernhard, 2009. "Price formation in electricity forward markets and the relevance of systematic forecast errors," Energy Economics, Elsevier, vol. 31(3), pages 356-364, May.
    18. Zarnikau, Jay & Hallett, Ian, 2008. "Aggregate industrial energy consumer response to wholesale prices in the restructured Texas electricity market," Energy Economics, Elsevier, vol. 30(4), pages 1798-1808, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Cédric Clastres & Haikel Khalfallah, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Post-Print hal-03193212, HAL.
    3. Hirth, Lion & Khanna, Tarun M. & Ruhnau, Oliver, 2024. "How aggregate electricity demand responds to hourly wholesale price fluctuations," Energy Economics, Elsevier, vol. 135(C).
    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).
    7. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, K.H. & Qi, H.S. & Tsai, C.H. & Woo, C.K. & Zarnikau, J., 2021. "Energy trading efficiency in the US Midcontinent electricity markets," Applied Energy, Elsevier, vol. 302(C).
    2. Zarnikau, J. & Woo, C.K. & Zhu, S. & Tsai, C.H., 2019. "Market price behavior of wholesale electricity products: Texas," Energy Policy, Elsevier, vol. 125(C), pages 418-428.
    3. Woo, C.K. & Chen, Y. & Olson, A. & Moore, J. & Schlag, N. & Ong, A. & Ho, T., 2017. "Electricity price behavior and carbon trading: New evidence from California," Applied Energy, Elsevier, vol. 204(C), pages 531-543.
    4. Zarnikau, J. & Tsai, C.H. & Woo, C.K., 2020. "Determinants of the wholesale prices of energy and ancillary services in the U.S. Midcontinent electricity market," Energy, Elsevier, vol. 195(C).
    5. Zarnikau, J. & Zhu, S. & Woo, C.K. & Tsai, C.H., 2020. "Texas's operating reserve demand curve's generation investment incentive," Energy Policy, Elsevier, vol. 137(C).
    6. Woo, C.K. & Milstein, I. & Tishler, A. & Zarnikau, J., 2019. "A wholesale electricity market design sans missing money and price manipulation," Energy Policy, Elsevier, vol. 134(C).
    7. Woo, C.K. & Moore, J. & Schneiderman, B. & Ho, T. & Olson, A. & Alagappan, L. & Chawla, K. & Toyama, N. & Zarnikau, J., 2016. "Merit-order effects of renewable energy and price divergence in California’s day-ahead and real-time electricity markets," Energy Policy, Elsevier, vol. 92(C), pages 299-312.
    8. Woo, C.K. & Shiu, A. & Liu, Y. & Luo, X. & Zarnikau, J., 2018. "Consumption effects of an electricity decarbonization policy: Hong Kong," Energy, Elsevier, vol. 144(C), pages 887-902.
    9. Hirth, Lion & Khanna, Tarun M. & Ruhnau, Oliver, 2024. "How aggregate electricity demand responds to hourly wholesale price fluctuations," Energy Economics, Elsevier, vol. 135(C).
    10. Maria Chiara D'Errico & Carlo Andrea Bollino, 2015. "Bayesian Analysis of Demand Elasticity in the Italian Electricity Market," Sustainability, MDPI, vol. 7(9), pages 1-22, September.
    11. Woo, C.K. & Zarnikau, J., 2019. "Renewable energy's vanishing premium in Texas's retail electricity pricing plans," Energy Policy, Elsevier, vol. 132(C), pages 764-770.
    12. Hirth, Lion & Khanna, Tarun & Ruhnau, Oliver, 2023. "How aggregate electricity demand responds to hourly wholesale price fluctuations," EconStor Preprints 272048, ZBW - Leibniz Information Centre for Economics.
    13. Adnan Haider Bukhari & Safdar Ullah Khan, 2008. "A Small Open Economy DSGE Model for Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(4), pages 963-1008.
    14. Richard S. J. Tol & In Chang Hwang & Frédéric Reynès, 2012. "The Effect of Learning on Climate Policy under Fat-tailed Uncertainty," Working Paper Series 5312, Department of Economics, University of Sussex Business School.
    15. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    16. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    17. Francesco Furlanetto & Francesco Ravazzolo & Samad Sarferaz, 2019. "Identification of Financial Factors in Economic Fluctuations," The Economic Journal, Royal Economic Society, vol. 129(617), pages 311-337.
    18. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    19. Liu, De-Chih & Chang, Yu-Chien, 2022. "Systematic variations in exchange rate returns," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 569-583.
    20. Hasan, Iftekhar & Horvath, Roman & Mares, Jan, 2020. "Finance and wealth inequality," Journal of International Money and Finance, Elsevier, vol. 108(C).

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:81:y:2019:i:c:p:259-272. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.