Nuclear Engineering and Technology (Aug 2017)

Statistical model for forecasting uranium prices to estimate the nuclear fuel cycle cost

  • Sungki Kim,
  • Wonil Ko,
  • Hyoon Nam,
  • Chulmin Kim,
  • Yanghon Chung,
  • Sungsig Bang

DOI
https://doi.org/10.1016/j.net.2017.05.007
Journal volume & issue
Vol. 49, no. 5
pp. 1063 – 1070

Abstract

Read online

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.

Keywords