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

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. •Examine impact of both day-ahead market (DAM) and real-time market (RTM) pricing on wholesale demand in deregulated electricity market•Bayesian, hierarchical population model replaces need for systems model.•Demand is highly sensitive for large DAM price increases compared to similar RTM price hikes.•Demand response to price volatilities is generally the same for the four major zonal markets in Texas.•One-day ahead prediction errors range from 1.2 to roughly 7% across the four markets.