Quantifying key uncertainties in the costs of nuclear power

Abstract

Summary In power system portfolio decisions, cost risk (uncertainty over cost) should be an important consideration, in addition to central estimates of cost. This study quantifies the uncertainty in each of the cost components for nuclear power, and combines them using a Monte Carlo analysis, allowing a direct assessment of cost risk for this technology. This can be used as an input to sophisticated portfolio optimisation modelling tools that take cost risk into account. Levelised cost of energy (LCOE) estimates are also provided here to allow an indicative comparison of the scale of cost risk, compared with other technologies. The most important contributors to cost risk for nuclear power generation are identified to be overnight capital cost (OCC) estimates, the degree of cost escalation over the construction and pre‐construction periods and the duration of those periods. In the absence of cost escalation, the mean LCOE of nuclear power is found to be AU$145/MWh in jurisdictions excluding Asia (or AU$130/MWh if Asian plant costs are included in the distributions), with a standard deviation of AU$62/MWh. However, when cost escalation over construction and pre‐construction periods is included at rates observed during nuclear build programs in France and the USA, the mean LCOE increases to AU$515/MWh, with a standard deviation of AU$2646/MWh. These results indicate that nuclear power costs have an 80% probability of exceeding AU$170/MWh, and a 50% probability of exceeding AU$278/MWh, based upon Monte Carlo analysis. This suggests that for OECD jurisdictions without an established nuclear industry (such as Australia), nuclear power may be comparable in cost with ‘dispatchable’, synchronous renewable alternatives such as concentrating solar thermal. Furthermore, the considerable cost risk associated with nuclear power is a significant disadvantage. Copyright © 2016 John Wiley & Sons, Ltd.

Integrated grey relational analysis and multi objective grey linear programming for sustainable electricity generation planning

“…Since, the Fukushima disaster, nuclear safety standards have been raised, and as a result led infrastructure costs to grow substantially (Boggard 2014). Furthermore, new reactor design innovations increase project completion and cost uncertainty (Riesz et al 2016). These issues and particularly the new increased costs have not yet been clearly incorporated in the literature and therefore are not taken into account into our modelling.…”

Simulation of Levelized Costs of Electricity Considering Externalities

“…The LCOE is useful to the strategic planning of a country's electric system, such as Australia's case. Riesz et al (Riesz, Sotiriadis, Vithayasrichareon, & Gilmore, 2017) used the LCOE to evaluate the economic viability of implementing a nuclear power plant construction program in Australia for the following two decades from the research and reducing CO2 emissions. Australia generates 80% of its electricity with coal-fired thermoelectric plants and has no nuclear power plants.…”

“…On the other hand, the Monte Carlo analysis has been used to solve uncertainties in LCOEs. Such as the case of Riesz et al (Riesz, Sotiriadis, Vithayasrichareon, & Gilmore, 2017) that used 10,000 Monte Carlo simulations that included overnight capital cost (OCC), the degree of cost escalation over the construction and pre-construction periods, and the duration of those periods. Since externalities are included in this research, the use of Monte Carlo analysis provides a better understanding of its impact on the LCOE.…”

Stakeholder perspectives on the cost requirements of Small Modular Reactors

“…According to Thomas (2005), the cost of capital could range between 5% to 15%, depending on the competitiveness of the electricity market, the utility, the country risk and the credit rating of the company. The uncertainty range of the LCOE of a NPP is driven by the selected cost of capital value (Riesz et al, 2017). The interest during construction is added to the overnight construction cost to produce a figure for total capital cost.…”