A Method to estimate the economy-wide consequences of widespread, long duration electric power interruptions

Ian Sue Wing, Peter H. Larsen (), Juan Pablo Carvallo, Alan Sanstad, Dan Wei, Adam Rose, Sunhee Baik, Jeremy Smith, Christopher Ramee and Ridge Peterson
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Ian Sue Wing: Boston University
Peter H. Larsen: Lawrence Berkeley National Laboratory
Juan Pablo Carvallo: Lawrence Berkeley National Laboratory
Alan Sanstad: Lawrence Berkeley National Laboratory
Dan Wei: University of Southern California
Adam Rose: University of Southern California
Sunhee Baik: Lawrence Berkeley National Laboratory
Jeremy Smith: California Energy Commission
Christopher Ramee: Resource Innovations Inc.
Ridge Peterson: Resource Innovations Inc.

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract We partnered with a utility in the U.S. state of Illinois to develop and pilot an approach to estimate the economic impacts of widespread, long duration (WLD) power interruptions. We surveyed their customers about hypothetical blackouts, identifying and classifying mitigating/resilience behaviors and quantifying their costs and benefits. Survey results are scaled up to the broader regional economy, and used to drive a computational general equilibrium (CGE) simulation of the effects of power interruptions and attendant customer responses (e.g., relocation, backup generation). Impacts are severe: 1-, 3-, and 14-day interruptions reduce the utility service area’s three-month GDP by $1.8 Bn (1.3%), $3.7 Bn (2.6%) and $15.2 Bn (10.4%), respectively, with losses driven overwhelmingly by disequilibrium responses to shortages as opposed to price signals (71%–88%). Doubling backup power penetration moderates GDP losses by 11%–14%, and is relatively least beneficial during the longest interruption duration. Results highlight previously unquantified economic losses that can potentially be avoided by investments in power system resilience.

Date: 2025
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DOI: 10.1038/s41467-025-58537-4

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