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This study focuses on the Electric Reliability Council of Texas (ERCOT) electricity market in Texas and demonstrates how the increase in temperature due to climate change is already driving large increases in electricity demand and total electricity costs. Results show that, compared to a 1950–80 baseline climate, electricity demand in 2023 was 1.9 GW (3.9%) higher because of the extreme temperatures of that year—climate change contributed 47% of this increase, with the rest coming from short-term climate variability. As demand increases, so does the price per unit of electricity, so consumers are hit double: They must buy more electricity, and each unit of electricity costs more. Using data from the wholesale market, we estimate that the total cost of electricity (the combination of higher demand and higher per unit prices) increased by $7.6B in 2023 compared to the baseline climate, $290 per ERCOT customer, with most of this increase occurring during the summer. Climate change contributed about 29% of this ($2.2B, $83 per customer), while short-term variability contributed the rest. About two-thirds of this increase is due to price increases triggered when the ERCOT grid becomes constrained. Investments in increasing the power supply or the ability to transmit it across the state, or reducing demand (e.g., demand response), could substantially reduce the impact of increasing temperature on the cost of electricity in Texas. Significance StatementQuantifying the impacts of warmer temperatures due to climate change on society is a key goal of the climate science community. In this paper, we develop a methodology for calculating the cost of increased temperatures on electricity consumption. We show that climate change is driving up the costs of electricity in Texas. Compared to the climate of the mid-twentieth century, electricity demand was 4.1% higher in 2023, with climate change responsible for about half of this increase. This increased the total cost of electricity by $7.6 billion, $290 per person. Climate change contributed about 29% of this extra cost, representing a significant burden on the poorest in our society.
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The Impact of Neglecting Climate Change and Variability on ERCOT’s Forecasts of Electricity Demand in Texas
Abstract The Electric Reliability Council of Texas (ERCOT) manages the electric power across most of Texas. They make short-term assessments of electricity demand on the basis of historical weather over the last two decades, thereby ignoring the effects of climate change and the possibility of weather variability outside the recent historical range. In this paper, we develop an empirical method 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 most severe weather events will use 100% of available power—if anything goes wrong, as it did during the 2021 winter, there will not be sufficient available power. More quantitatively, 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. The shortage of power on the ERCOT grid is partially hidden by the fact that ERCOTs seasonal assessments, which are based entirely on historical weather, are too low. Prior to the 2021 winter blackout, ERCOT forecast 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.
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- Award ID(s):
- 1841308
- PAR ID:
- 10333308
- Date Published:
- Journal Name:
- Weather, Climate, and Society
- Volume:
- 14
- Issue:
- 2
- ISSN:
- 1948-8327
- Page Range / eLocation ID:
- 499 to 505
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1175/WCAS-D-21-0140.1
