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

Paul Damien, Ruth Fuentes-García, Ramsés H. Mena and Jay Zarnikau ()

Energy Economics, 2019, vol. 81, issue C, 259-272

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.

Keywords: Electricity demand; Energy forecast; Price effects; Bayesian inference (search for similar items in EconPapers)
JEL-codes: L51 L94 L97 Q02 Q41 Q47 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:81:y:2019:i:c:p:259-272

DOI: 10.1016/j.eneco.2019.04.008

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