Hedging against uncertainty in the nuclear fuel cycle

Time-dependent analyses of the nuclear economy, for instance to assess transitions between nuclear fuel cycles, often confront uncertainties by implementing a scenario-based approach in which uncertain variables are parametrically varied. Yet the uncertainties surrounding important state variables-demand growth rates, dates of technology availability, technology costs- will likely remain unresolved for decades. Strong transition strategies should be flexible, enabling reasonable outcomes to be attained once the uncertainty is resolved. This paper demonstrates a decision tree analysis methodology for incorporating uncertainties into the process of developing transition strategies. The method derives hedging strategies, defined as strategies which retain the greatest flexibility for adjustment once uncertainties are resolved. A case study involving transition from a once-through cycle to continuous recycle in fast reactors is presented, in which the future cost of used fuel and high level waste disposal are subject to uncertainty. Transition strategies, consisting of reprocessing facility construction and reactor deployment schedules are simulated using VEGAS, a lightweight fuel cycle mass balance simulation model. From these, a hedging strategy is chosen with the aim of minimizing the integrated cost of electricity (COE) over the remainder of the century in light of disposal cost uncertainties which will not be resolved until 2060. The hedging strategy minimizes the amount by which the strategy's COE exceeds the value that could have been achieved had perfect information about disposal costs been available from the beginning. By explicitly including uncertainties in the decision-making algorithm, the method places high value on strategies whose early steps preserve many courses of action as information becomes available.