An official website of the United States government
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.
more »
« less
This content will become publicly available on April 1, 2026
Climate Change Increases Energy Demand and Cost in Texas
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.
more »
« less
- Award ID(s):
- 2243602
- PAR ID:
- 10611548
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Weather, Climate, and Society
- Volume:
- 17
- Issue:
- 2
- ISSN:
- 1948-8327
- Page Range / eLocation ID:
- 153 to 160
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Gentry, E; Ju, F; Liu, X (Ed.)This research investigates optimal pricing strategies in a service-providing queueing system where customers may renege before service completion. Prices are quoted upon customer arrivals and the incoming customers join the system if their willingness to pay exceeds the quoted price. While waiting in line or during service, customers may get impatient and leave without service, incurring an abandonment cost. There is also a per-unit time per-customer holding cost. Our objective is to maximize the long-run average profit through optimal pricing policies. We model the problem as a Markov decision process and identify the optimal pricing using policy iteration. We also study the structure of the optimal pricing policy. Furthermore, we show that under mild assumptions, the optimal price increases as the number of customers in the system increases. When those assumptions do not hold, optimal price decreases and then increases as the number of customers in the system grows.more » « less
-
Gentry, E; Ju, F; Liu, X (Ed.)This research investigates optimal pricing strategies in a service-providing queueing system where customers may renege before service completion. Prices are quoted upon customer arrivals and the incoming customers join the system if their willingness to pay exceeds the quoted price. While waiting in line or during service, customers may get impatient and leave without service, incurring an abandonment cost. There is also a per-unit time per-customer holding cost. Our objective is to maximize the long-run average profit through optimal pricing policies. We model the problem as a Markov decision process and identify the optimal pricing using policy iteration. We also study the structure of the optimal pricing policy. Furthermore, we show that under mild assumptions, the optimal price increases as the number of customers in the system increases. When those assumptions do not hold, optimal price decreases and then increases as the number of customers in the system grows.more » « less
-
Abstract The United States (U.S.) West Coast power system is strongly influenced by variability and extremes in air temperatures (which drive electricity demand) and streamflows (which control hydropower availability). As hydroclimate changes across the West Coast, a combination of forces may work in tandem to make its bulk power system more vulnerable to physical reliability issues and market price shocks. In particular, a warmer climate is expected to increase summer cooling (electricity) demands and shift the average timing of peak streamflow (hydropower production) away from summer to the spring and winter, depriving power systems of hydropower when it is needed the most. Here, we investigate how climate change could alter interregional electricity market dynamics on the West Coast, including the potential for hydroclimatic changes in one region (e.g., Pacific Northwest (PNW)) to “spill over” and cause price and reliability risks in another (e.g., California). We find that the most salient hydroclimatic risks for the PNW power system are changes in streamflow, while risks for the California system are driven primarily by changes in summer air temperatures, especially extreme heat events that increase peak system demand. Altered timing and amounts of hydropower production in the PNW do alter summer power deliveries into California but show relatively modest potential to impact prices and reliability there. Instead, our results suggest future extreme heat in California could exert a stronger influence on prices and reliability in the PNW, especially if California continues to rely on its northern neighbor for imported power to meet higher summer demands.more » « less
-
Abstract In the United States, thermal power plant electrical generators (EGs) are large water diverters and consumptive users who need water for cooling. Retrofitting existing cooling systems to dry cooling and building new facilities with dry cooling can save water and reduce EG's vulnerability to drought. However, this can be an expensive source of water. We estimate that the cost of water saved by retrofitting cooling in existing EGs ranges from $0.04/m3to $18/m3depending on facility characteristics. Also water savings from building new EGs with dry cooling ranges in cost per unit water from $1.29/m3to $2.24/m3. We compare costs with that for water development projects identified in the Texas State Water Plan. We find the water cost from converting to dry cooling is lower than many of the water development possibilities. We then estimate the impact of climate change on the cost of water saved, finding climate change can increase EG water use by up to 9.3% and lower the costs of water saved. Generally, it appears that water planners might consider cooling alterations as a cost competitive water development alternative whose cost would be further decreased by climate change.more » « less
