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Publication Date
1 January 2023

Projecting Future Energy Production From Wind Farms – Part 1

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New WRF simulations nested within the Max Planck Institute global model are used to quantify possible changes in annual electricity drought and the occurrence of production droughts (extended periods with anonymously low power generation) in the current and current climate. Changes are generally negative (lower production), regionally specific, and are of smaller magnitude than historical trends due to technology innovation towards increased production.


Wind energy represents 29% of total U.S. electricity generation capacity additions over the last decade with installed capacity rising to 135 GW at the end of 2021. We quantify possible changes in electricity production from wind in different regions of the US that might arise due to greenhouse gas-induced climate change.


New simulations at 12 km grid-spacing with the Weather and Research Forecasting (WRF) model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential over the US as a result of global warming. Annual capacity factors (CF, measures of electrical power production) computed using WRF output are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65 and the root mean square error is 5.4 percentage points. Output from the MPI-WRF model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CFA) indicate no change to 2050 in the Southern Great Plains and Northeast. In the Midwest inter-annual variability of CFA increases and CFA decline by up to 2 percentage points in the Northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern U.S. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, while the converse is true over the Northern Great Plains.

For a wind farm with the mean installed capacity of those considered here of 170 MW, assuming CFA of 40% in the contemporary climate, the annual revenue is ~ $20 million and a 1 percentage point increase or decrease in CFA equates to a $200,000 change in revenue for the mean wind farm considered in this study. Hence, there is clear value in continuing efforts to make more robust projections of wind climate variability and change to select optimal locations for future wind energy installations. It is also useful to contextualize the projected differences in CFA in historical gains in CF due to technology advances (e.g. increased wind turbine reliability). Technology-driven changes over the last 3 decades have led to an average annualized increase in CFA of approximately 0.75 percentage points per year. These historical changes in CFA thus greatly exceed projected changes in CFA due to global climate non-stationarity.

Point of Contact
Sara C Pryor
Cornell University
Funding Program Area(s)
Additional Resources:
NERSC (National Energy Research Scientific Computing Center)