Each year the U.S. government makes significant investments in improving weather forecast models. In this paper, we use a multidisciplinary approach to examine how utilities can benefit from improved wind-speed forecasts to more efficiently use wind-generated electricity and subsequently increase economic activity. Specifically, we examine how improvements to the National Oceanic and Atmospheric Administration's high-resolution rapid refresh model (HRRR) wind forecasts can provide (1) cost savings for utilities and (2) increase in real household income. To do so, we compare 12-h-ahead wind forecasts with real-time observations for two HRRR model transitions (i.e., when one model is operational, the other is being tested). We compare estimates of actual and predicted wind power under the publicly available and developmental models, with reduced forecast errors allowing for better utility decision-making and lower production costs. We then translate potential cost savings into electricity price changes, which are entered as exogenous shocks to eight regional computable general equilibrium models constructed for the U.S. Overall, we find that households would have seen a potential $60 million increase in real income for our sample (13% of all contiguous U.S. land-based turbine capacity), which had the updated HRRR models been in place during the two transition periods; applying our estimated savings for the sample of turbines to the entire array of turbines shows a potential real household income increase in approximately $384 million during these time frames.
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Research Article|
May 17 2022
Estimating the economic impacts of improved wind speed forecasts in the United States electricity sector
Hwayoung Jeon;
Hwayoung Jeon
1
Colorado State University
, Fort Collins, Colorado 80523, USA
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Brad Hartman
;
Brad Hartman
1
Colorado State University
, Fort Collins, Colorado 80523, USA
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Harvey Cutler;
Harvey Cutler
1
Colorado State University
, Fort Collins, Colorado 80523, USA
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Rebecca Hill;
Rebecca Hill
1
Colorado State University
, Fort Collins, Colorado 80523, USA
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Yuchen Hu;
Yuchen Hu
1
Colorado State University
, Fort Collins, Colorado 80523, USA
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Tao Lu;
Tao Lu
1
Colorado State University
, Fort Collins, Colorado 80523, USA
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Martin Shields
;
Martin Shields
a)
1
Colorado State University
, Fort Collins, Colorado 80523, USA
a)Author to whom correspondence should be addressed: martin.shields@colostate.edu
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David D. Turner
David D. Turner
2
NOAA Global Systems Laboratory
, Boulder, Colorado 80305-3328, USA
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a)Author to whom correspondence should be addressed: martin.shields@colostate.edu
J. Renewable Sustainable Energy 14, 036101 (2022)
Article history
Received:
December 10 2021
Accepted:
March 24 2022
Citation
Hwayoung Jeon, Brad Hartman, Harvey Cutler, Rebecca Hill, Yuchen Hu, Tao Lu, Martin Shields, David D. Turner; Estimating the economic impacts of improved wind speed forecasts in the United States electricity sector. J. Renewable Sustainable Energy 1 May 2022; 14 (3): 036101. https://doi.org/10.1063/5.0081905
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