Long-term Stochastic Forecasting of the Nuclear Energy Global Market

Vladimir Kharitonov (), Uliana Kurelchuk () and Sergey Masterov ()
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Vladimir Kharitonov: National Research Nuclear University ‘MEPhI’ (NRNU MEPhI), Russia
Uliana Kurelchuk: National Research Nuclear University ‘MEPhI’ (NRNU MEPhI), Russia
Sergey Masterov: NIAEP–ASE (Atomstroyexport) united company (Russia)

Foresight and STI Governance (Foresight-Russia till No. 3/2015), 2015, vol. 9, issue 2, 58-71

Abstract: The paper addresses the issue of long-term forecasting of the global nuclear power market and opportunities for studying its individual sections. Given the current state of the market and related industries, a scientific approach to strategic forecasting based on evaluating dispersions of forecasts acquires particular significance. The authors first developed and applied a probabilistic forecasting technique to a number of market indicators of the global nuclear power industry in real terms for the period up to 2035. In particular, the calculations concern the number and electric capacity of input-output nuclear power plants; and the demand for natural and enriched uranium and enrichment services. The forecasting is based on stochastic modeling of NPP lifecycles and exploitation parameters, uranium enrichment rate, and nuclear energy planes in the different regions. The proposed model, as opposed to scenario approaches, means that the probability distributions of mentioned values can be calculated. This is of crucial importance in assessing the economic risks for various economic agents operating in the world nuclear technology market. The results of modeling the main indicators of nuclear power markets (the dynamics of the net electric capacity of nuclear power plants worldwide and across the largest regions) are consistent with the scenario forecasts provided by WNA and IAEA (2013), which are based on data provided by the members of these organizations. This fact indicates the correct choice of the model for describing the frequency distributions of the key stages of reactor ‘arbor vitae’. The authors modeled the likely volumes of the market for constructing new NPP and taking the stopped ones off the road for the next 15 year period in the different regions, Russia and worldwide. Finally, the paper estimates the likely share of the new Russian designed NPP construction in the world market for the period up to 2030.

Keywords: stochastic forecasting; nuclear energy market; NPP net capacity; NPP construction; NPP decommissioning; natural and enriched uranium; uranium isotopes separative work; Monte-Carlo simulation; dispersion (search for similar items in EconPapers)
JEL-codes: C15 C87 Q47 Q49 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hig:fsight:v:9:y:2015:i:2:p:58-71

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