Elicitation results for large-scale Gen
Figure 1. Elicitation results for large-scale Gen. III/III+ reactor systems for the FEEM, Harvard, and CMU studies (Abdulla et al 2013, Anadon et al 2012). The data points represent the 50th percentile estimates. The top and bottom error bars denote the 10th and 90th percentiles, respectively. The '2010 ref.' data point includes the experts' estimates of costs in 2010, of interest given the fact that there are few reactors being built in both the US and the EU. CMU experts 6 and 8 did not provide a 50th percentile estimate.
Characterization of the anticipated performance of energy technologies to inform policy decisions increasingly relies on expert elicitation. Knowledge about how elicitation design factors impact the probabilistic estimates emerging from these studies is, however, scarce. We focus on nuclear power, a large-scale low-carbon power option, for which future cost estimates are important for the design of energy policies and climate change mitigation efforts. We use data from three elicitations in the USA and in Europe and assess the role of government research, development, and demonstration (RD&D) investments on expected nuclear costs in 2030. We show that controlling for expert, technology, and design characteristics increases experts' implied public RD&D elasticity of expected costs by 25%. Public sector and industry experts' cost expectations are 14% and 32% higher, respectively than academics. US experts are more optimistic than their EU counterparts, with median expected costs 22% lower. On average, a doubling of public RD&D is expected to result in an 8% cost reduction, but the uncertainty is large. The difference between the 90th and 10th percentile estimates is on average 58% of the experts' median estimates. Public RD&D investments do not affect uncertainty ranges, but US experts are less confident about costs than Europeans.