Future costs of key low-carbon energy technologies: Harmonization and aggregation of energy technology expert elicitation data

Abstract

Abstract.In this paper we standardize, compare, and aggregate results from thirteen surveys of technology experts, performed over a period of five years using a range of different methodologies, but all aiming at eliciting expert judgment on the future cost of five key energy technologies and how future costs might be influenced by public R&D investments. To enable researchers and policy makers to use the wealth of collective knowledge obtained through these expert elicitations we develop and present a set of assumptions to harmonize them. We also aggregate expert estimates within each study and across studies to facilitate the comparison. The analysis showed that, as expected, technology costs are expected to go down by 2030 with increasing levels of R&D investments, but that there is not a high level of agreement between individual experts or between studies regarding the technology areas that would benefit the most from R&D investments. This indicates that further study of prospective cost data may be useful to further inform R&D investments. We also found that the contributions of additional studies to the variance of costs in one technology area differed by technology area, suggesting that (barring new information about the downsides of particular forms of elicitations) there may be value in not only including a diverse and relatively large group of experts, but also in using different methods to collect estimates.

Sensitivity to Energy Technology Costs: A Multi-Model Comparison Analysis

“…We set out using as an input to integrated assessment models the results from the aggregated expert elicitations data described in (Baker et al, 2014a).…”

Expert elicitation survey on future wind energy costs

“…Its use was explicitly called for in a review of the IPCC [39] and by a National Academies review of the U.S. Department of Energy [40]. Expert elicitation is increasingly common as a tool for making estimates of the future costs of energy technologies [32,41]. However, formal elicitation procedures have not yet been widely applied to understand wind energy costs [42][43].…”

Sensitivity to energy technology costs: A multi-model comparison analysis

“…By harmonizing and aggregating the data across experts and across surveys by means of the process described in (Baker, 2014a), we obtain eight probability distributions representing the values of these uncertain metrics (summary statistics for the distributions are reported in Table 1). We generate 740 scenarios, representing combinations of technology performances drawn from these eight cost distributions.…”

“…Therefore, the effort of harmonizing the data across surveys has represented a complex endeavor which is fully described in Baker et al (2014a). The resulting estimates span a wide array of uncertainties including those that might be related to different methodology employed to collect the data from experts.…”