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An Ex-Ante Method to Verify Commercial U.S. Nuclear Power Plant Decommissioning Cost Estimates
Discussion paper / Internet publication
 
ID 4651146
Digital Object Identifier DOI 10.2139/ssrn.4112957
Author(s) Lordan-Perret, Rebecca; Bärenbold, Rebekka; Weigt, Hannes; Rosner, Robert
Author(s) at UniBasel Lordan-Perret, Rebecca
Bärenbold, Rebekka
Weigt, Hannes
Year 2022
Month and day 11-10
Year: comment 2022
Title An Ex-Ante Method to Verify Commercial U.S. Nuclear Power Plant Decommissioning Cost Estimates
Series title WWZ Working Paper
Volume 2022
Number 08
Pages 21
Publisher / Institution WWZ
Keywords nuclear power; decommissioning; cost estimation; contingency; Wilks' formula; reference class forecasting
Abstract There are billions of dollars at stake in the US nuclear power plant decommissioning market. Approximately 100 nuclear power plants are still operating but will come offline and need to be decommissioned over the next few decades. The US Nuclear Regulatory Commission (NRC) mandates that the operators of these plants set money aside in segregated funds to finance decommissioning work. However, it is hard for external stakeholders to verify the cost estimations, which ultimately determine how much operators are required to save. In this paper, we develop a method to validate the existing cost models and calculate a contingency empirically for these models. We extend Reference Class Forecasting methods using adaptive kernel fitting and the Wilks' formula. Based on this method, and assuming a social tolerance for potential cost overruns of 20%, we calculate a new contingency of 48% of the estimated radiological decommissioning cost. After a "stress test" of the current decommissioning trust funds of operating reactor sites, we find that 48% of reactors we considered have sufficient funding-in many cases substantially more than required-and could therefore finance the potential scale of overrun. However, we find that 28 plants (52%) would fall short on average $211 million. Still, overruns at every plant are not a foregone conclusion because-while overruns are probable, based on past experience-the actual scale and frequency is not known. Nevertheless, our results add further evidence to the mounting call for the NRC to revise its cost models in light of new information.
edoc-URL https://edoc.unibas.ch/90289/
Full Text on edoc Available
 
   

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