Economic potential of fuel recycling options: A lifecycle cost analysis of future nuclear system transition in China. (February 2017) - Gao, Ruxing; Choi, Sungyeol; Il Ko, Won; Kim, Sungki
Abstract: In today's profit-driven market, how best to pursue advanced nuclear fuel cycle technologies while maintaining the cost competitiveness of nuclear electricity is of crucial importance to determine the implementation of spent fuel reprocessing and recycling in China. In this study, a comprehensive techno-economic analysis is undertaken to evaluate the economic feasibility of ongoing national projects and the technical compatibility with China's future fuel cycle transition. We investigated the dynamic impacts of technical and economic uncertainties in the lifecycle of a nuclear system. The electricity generation costs associated with four potential fuel cycle transition scenarios were simulated by probabilistic and deterministic approaches and then compared in detail. The results showed that the total cost of a once-through system is lowest compared those of other advanced systems involving reprocessing and recycling. However, thanks to the consequential uncertainties caused by the further progress toward technology maturity, the economic potential of fuel recycling options was proven through a probabilistic uncertainty analysis. Furthermore, it is recommended that a compulsory executive of closed fuel cycle policy would pose some investment risk in the near term, though the execution of a series of R&D initiatives with a flexible roadmap would be valuable in the long run. Highlights: Real-time economic performance of the four scenarios of China's nuclear fuel cycle system transition until 2100. Systematic assessments of techno-economic feasibility for ongoing national reprocessing projects. Investigation the cost impact on nuclear electricity generation caused by uncertainties through probabilistic analysis. Recommendation for sustainable implementation of fuel cycle R&D initiative ingrate with flexible roadmap in the long run.