Autonomous dynamic decision making in a nuclear fuel cycle simulator

Abstract

Growing energy demand and the push to move toward carbon-free ways of electricity generation have renewed the world's interest in nuclear energy. Due to the high technical and economic uncertainties related to nuclear energy, simulation tools have become a necessity in order to plan and evaluate possible nuclear fuel cycles (NFCs). Most of the NFC simulators today work by running the simulation with a user-defined set of facility build orders and preferences. While this allows for a simple way to change the simulation conditions, it may not always lead to optimal results and strongly relies on the user defining the correct parameters. This study looks into the possibility of using the expected cost of electricity (CoE) as the driving build decision variable instead of relying on user-defined build orders. This is a first step toward a more general decision making strategy in dynamic fuel cycle simulation. For this purpose, additional modules were implemented in an NFC simulator, VEGAS, with the consumption dependent price of uranium as a time-varying NFC cost component that drives the cost competitiveness of available NFC options. The model was demonstrated to verify the correct operation of a CoE-driven NFC simulator.