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Determining Optimal Used Fuel Allocation Strategies

Gordon M. Petersen, Steven E. Skutnik, James Ostrowski, Robert A. Joseph, III

Nuclear Technology / Volume 200 / Number 3 / December 2017 / Pages 208-224

Technical Paper /

Received:June 26, 2017
Accepted:September 1, 2017
Published:November 16, 2017

A key challenge in fulfilling the U.S. federal government’s obligations under the Nuclear Waste Policy Act is in the transition of used nuclear fuel (UNF) storage away from at-reactor storage and to a consolidated interim storage facility (CISF). The default strategy (Standard Contract) for the U.S. Department of Energy is to use the oldest fuel first (OFF) allocation strategy, which would entail the federal government prioritizing UNF shipments based on fuel discharge date with the option to prioritize shutdown sites. This may not be the most cost-efficient model given the extensive amount of UNF already at reactor sites. Currently, there is no way to preemptively remove fuel from sites that may be close to shutdown or have a higher storage or potential storage cost. As wet storage pools at reactors continue to fill to capacity at operating reactors, the backlog of UNF shipments to the CISF places additional pressure on operators to expand at-reactor dry storage capacity, thus adding to total system costs.

An essential aspect of this transition is in developing appropriate analytical tools to evaluate the effect of factors such as fuel shipment prioritization, logistics, and associated expenses. Examples of this would include evaluating fuel offloading prioritization strategies (OFF versus shutdown sites first), strategies to minimize transfer of UNF to dry storage (i.e., through direct shipment from cooling pools to the CISF), etc.

By applying integer programming techniques, it is possible to make a rigorous analytical determination of a UNF removal allocation strategy that minimizes the total number of shutdown reactor years (SRYs). Our findings indicate that an optimal unloading strategy can result in a threefold reduction in total system SRYs compared with an OFF-based queue, for a systemwide savings of about $8 billion.

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