Jangho Lee , Andrew Dessler

The Electric Reliability Council of Texas (ERCOT) manages the electric power across most of Texas. They make short-term assessments of electricity demand based on historical weather over the last decade or two, thereby ignoring the effects of climate change and the possibility of weather variability outside of the recent historical range. In this paper, we develop an empirical methodology to predict the impact of weather on energy demand. We use that with a large ensemble of climate model runs to construct a probability distribution of power demand on the ERCOT grid for summer and winter 2021. We find that the ERCOT grid is running with no safety margin, particularly during summer. We estimate a 5% chance that maximum power demand would be within 4.3 and 7.9 GW of ERCOT’s estimate of best-case available resources during summer and winter 2021, respectively, and a 20% chance it would be within 7.1 and 17 GW. With such small margins, the unexpected reductions in available power can lead to shortages on the grid. This problem is partially hidden by the fact that ERCOTs seasonal assessments, based entirely on historical weather, are too low. Prior to the 2021 winter blackout, ERCOT forecasted an extreme peak load of 67 GW. In reality, we estimate hourly peak demand was 82 GW, 22% above ERCOT’s most extreme forecast and about equal to the best-case available power. Given the high stakes, ERCOT should develop probabilistic estimates using modern scientific tools to predict the range of power demand more accurately.