Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost

  • Kim, Sungki (Nuclear Fuel Cycle Analysis, Korea Atomic Energy Research Institute) ;
  • Ko, Wonil (Nuclear Fuel Cycle Analysis, Korea Atomic Energy Research Institute) ;
  • Nam, Hyoon (Nuclear Fuel Cycle Analysis, Korea Atomic Energy Research Institute) ;
  • Kim, Chulmin (Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology) ;
  • Chung, Yanghon (Department of Business and Technology Management, Korea Advanced Institute of Science and Technology) ;
  • Bang, Sungsig (Department of Business and Technology Management, Korea Advanced Institute of Science and Technology)
  • Received : 2017.02.21
  • Accepted : 2017.05.01
  • Published : 2017.08.25
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Abstract

This paper presents a method for forecasting future uranium prices that is used as input data to calculate the uranium cost, which is a rational key cost driver of the nuclear fuel cycle cost. In other words, the statistical autoregressive integrated moving average (ARIMA) model and existing engineering cost estimation method, the so-called escalation rate model, were subjected to a comparative analysis. When the uranium price was forecasted in 2015, the margin of error of the ARIMA model forecasting was calculated and found to be 5.4%, whereas the escalation rate model was found to have a margin of error of 7.32%. Thus, it was verified that the ARIMA model is more suitable than the escalation rate model at decreasing uncertainty in nuclear fuel cycle cost calculation.

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