Endogenizing the probability of nuclear exit in an optimal power-generation mix model

Takanobu Kosugi

Energy, 2016, vol. 100, issue C, 102-114

Abstract: A major accident at a nuclear power reactor can lower public acceptance of this energy source and may result in a nuclear exit. This paper proposes an optimal power-generation planning model that deals explicitly with the costs involved in changing the power-generation mix due to a nuclear exit. The model introduces the probability of a major accident leading to a nuclear exit at a future time period as an endogenous variable, which is determined depending on the amount of nuclear power being generated during the preceding period. The proposed model is formulated as a stochastic programming problem that aims to minimize the expected value of overall power-generation costs computed with a weighted probability of every future state, branched according to a possible nuclear exit at each time period. An application of the model quantitatively implies that less nuclear dependency is optimal for a higher assumed frequency of a major accident per generated unit of electrical energy from nuclear—not only for the cost of direct damage from the accident, but largely because of the increased cost of overall power generation due to the subsequent nuclear exit. To put it differently, lowering the frequency of a major nuclear accident per reactor·year brings benefits exceeding the conventionally perceived effect of reducing an accident's direct damage. Lowering the major accident frequency to one per 106 reactor·years would free the optimal planning of future electricity supply from influence of an accident causing nuclear exit, if the geographical scale of the exit were limited to one-twentieth of the entire world.

Keywords: Energy modeling; Nuclear power phase-out; Stochastic programming; Energy economics; Carbon emission constraint (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:100:y:2016:i:c:p:102-114

DOI: 10.1016/j.energy.2016.01.083

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