Impacts of day-ahead versus real-time market prices on wholesale electricity demand in Texas
Ramsés H. Mena and
Jay Zarnikau ()
Energy Economics, 2019, vol. 81, issue C, 259-272
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: Q41 Q47 Q02 L94 L97 L51 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:81:y:2019:i:c:p:259-272
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