Future Prospects for Energy Technologies: Insights from Expert Elicitations

Abstract

Expert elicitation is a process for eliciting subjective probability distributions from experts about items of interest to decision makers. These methods have been increasingly applied in the energy domain to collect information on the future cost and performance of specific energy technologies and the associated uncertainty. This article reviews the existing expert elicitations on energy technologies with three main objectives: (1) to provide insights on expert elicitation methods and how they compare/complement other approaches to inform public energy decision making; (2) to review all recent elicitation exercises about future technology costs; and (3) to discuss the main results from these expert elicitations, in terms of implied rates of cost reduction and the role of R&D investments in shaping these reductions, and compare it with insights from backward looking approaches. We argue that the emergence of data on future energy costs through expert elicitations provides the opportunity for more transparent and robust analyses incorporating technical uncertainty to assess energy and climate change mitigation policies.

Integrating uncertainty into public energy research and development decisions

“…For example, the prices in solar PV electricity in Barbose et al 114 are lower than all but the most optimistic experts in the meta-analysis of solar elicitations by Verdolini et al 23 . A similar preliminary finding on the faster rate of decrease of solar PV in particular periods is shown in Verdolini et al 19 ). Even once sufficient time has passed, it is difficult to evaluate the accuracy of elicitations that are conditional on things like R&D investments since the conditions may have changed.…”

“…Verdolini et al 19 provide a review of 29 expert elicitation studies performed between 2007 and 2012, covering eleven energy technology categories. The range of studies reviewed there (plus two additional recent wind studies, making a total of 31 papers) are summarized in Table 1 and the key challenges and gaps associated with energy technology expert elicitations are summarized in Box 2.…”

“…The uncertainty characterized by elicitations goes beyond the uncertainty estimated from forecasting methods based on historical data (for example, learning or experience curves, as a function of deployment 20 or of time 19 ). For example, using 20-year windows of historical data on solar photovoltaic (PV) module costs from Fraunhofer 21 , the average annual cost reduction ranges between 2.7% and 4.6%, depending on the start date of the window; the average annual cost reduction over a 25-year period (1980-2015) is 2.8%.…”

“…When comparing the rate of change in the future cost of technologies implied by the expert elicitation studies of projections based on historical data, it was found 19 that the technologies differ in the degree to which the experts see the future as being similar to the past. For example, the median expert forecasts for nuclear power and biofuels are similar to historical data, while expert forecasts for bioelectricity are relatively pessimistic.…”

From Integrated to Integrative: Delivering on the Paris Agreement

“…Being the driving forces of these transitions required towards transforming our societies and economies, each and every one of these stakeholder groups should lie at the heart of policy support-including modelling-processes, especially in the context of an ongoing and systematic review and reshaping of climate action. Besides, recent pieces of literature suggest that gathering information, input, and preferences from a wide range of experts and including them in modelling activities significantly contributes to both transparency and robustness [23].…”