Integrating uncertainty into public energy research and development decisions

Abstract

P redicting the future is extremely difficult 1 , yet it is nonsensical to ignore the knowledge and understanding we can acquire from experts when making decisions. It is well understood that using experts, and using them wisely, is a key component of evidence-based policymaking 2 .In the energy sector, policymakers are faced with a number of near-term decisions, such as balancing technology R&D, performance standards, and subsidies; or designing energy technology R&D portfolios. Designing these policies involves managing the significant uncertainty that exists about how technologies will evolve with and without different policies 3 . In the wake of the December 2015 Paris Agreement, in which countries agreed to put in place national action plans to reduce greenhouse-gas emissions, and in the context of tight government budgets around the world, designing robust and cost-effective energy innovation policies in the face of technological uncertainty has become more pressing 4 . The question of how to design portfolios of R&D investments across a range of energy technologies has received much attention, most recently after the launch of the Mission Innovation and Breakthrough Energy Coalition pledges to increase public energy R&D funding and follow-on private investments in energy technologies. The R&D decision literature typically approaches this problem in two stages: first considering how R&D investments affect future technology costs 5 , then considering how future technology costs affect energy and climate policies (for example, EMF28; ref. 6).One method for informing policy decisions is to perform expert elicitations (a structured process for eliciting subjective probability distributions from subject-matter experts 7 ). Over the past 10 years, a number of researchers have performed expert elicitations to characterize the uncertainty around future cost and performance of various energy technologies, often subject to assumptions about public R&D investments. This information, however, is just one of the pieces of analysis needed to inform the design of optimal energy R&D Integrating uncertainty into public energy research and development decisions Laura Díaz Anadón 1,2 † *, Erin Baker 3 † and Valentina Bosetti 4,5 † Public energy research and development (R&D) is recognized as a key policy tool for transforming the world's energy system in a cost-effective way. However, managing the uncertainty surrounding technological change is a critical challenge for designing robust and cost-effective energy policies. The design of such policies is particularly important if countries are going to both meet the ambitious greenhouse-gas emissions reductions goals set by the Paris Agreement and achieve the required harmonization with the broader set of objectives dictated by the Sustainable Development Goals. The complexity of informing energy technology policy requires, and is producing, a growing collaboration between different academic disciplines and practitioners. Three analytical components have emerged to support the ...

Rescue US energy innovation

“…34 Finally, new analytical approaches to energy innovation policy could lead to better decisions regarding the allocation of energy RD&D investments across technology areas, leading to a more coherent and strategic portfolio approach. 35,36 Having said this, every study we know of has concluded that these kinds of improvements need to be accompanied by a substantial increase in total public funding for energy-technology innovation, if the immense challenges at the intersection of energy supply, the economy, public health, and the global climate are to be met. Deep cuts would be folly.…”

Characterization of Historical Methane Occurrence Frequencies from U.S. Underground Natural Gas Storage Facilities with Implications for Risk Management, Operations, and Regulatory Policy

“…Such drawbacks to the use of mean arithmetic ratios for various quantities are well known (California Council on Science and Technology, ; Paté‐Cornell, ; Savage, ). Accordingly, more robust methods to assess risk scenarios have therefore been developed and applied in various industries such as financial planning (Savage & Kavanagh, ), underground rock engineering (Brown, ), probabilistic seismic hazard analysis (Baker & Gupta, ), floating LNG platforms (Yeo et al., ), nuclear energy (Payne et al., ), energy policy (Anadón, Baker, & Bosetti, ), and public utilities (Alen et al., ).…”

“…more robust methods to assess risk scenarios have therefore been developed and applied in various industries such as financial planning (Savage & Kavanagh, 2014), underground rock engineering (Brown, 2012), probabilistic seismic hazard analysis (Baker & Gupta, 2016), floating LNG platforms (Yeo et al, 2016), nuclear energy (Payne et al, 2017), energy policy (Anadón, Baker, & Bosetti, 2017), and public utilities (Alen et al, 2016).…”

Uncertainty, politics, and technology: Expert perceptions on energy transitions in the United Kingdom

“…Assuming that the future can be predicted and designing policies accordingly, with only a limited number of variations, has been likened to "dancing on the top of a needle" [81] producing solutions that are optimal "only if all the assumptions made about the future turn out to be correct" and which "may fail in the face of inevitable surprise" [21]. It is suggested that a more robust alternative is to implement a multi-stage or iterative decision making process where assumptions are revisited continually as uncertainties are revealed [82][83][84]. This is sometimes conceived of as "dynamic adaptive" policymaking, with existing examples of these approaches being found in the flood risk planning [85,86] and transport [87] domains.…”