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

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 enginee...

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Bibliographic Details
Published in:Nuclear engineering and technology 2017, 49(5), , pp.1063-1070
Main Authors: Kim, Sungki, Ko, Wonil, Nam, Hyoon, Kim, Chulmin, Chung, Yanghon, Bang, Sungsig
Format: Article
Language:English
Subjects:
ARIMA Model
Cost Driver
Forecasting
Nuclear Fuel Cycle Cost
Uranium Price
원자력공학
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Summary: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.
ISSN:1738-5733
2234-358X
DOI:10.1016/j.net.2017.05.007