气候变化领域集成服务门户(CCPortal): Comparing expert elicitation and model-based probabilistic technology cost forecasts for the energy transition

CCPortal

DOI	10.1073/pnas.1917165118
	Comparing expert elicitation and model-based probabilistic technology cost forecasts for the energy transition
	Meng J.; Way R.; Verdolini E.; Anadon L.D.
发表日期	2021
ISSN	0027-8424
卷号	118 期号:27
英文摘要	We conduct a systematic comparison of technology cost forecasts produced by expert elicitation methods and model-based methods. Our focus is on energy technologies due to their importance for energy and climate policy. We assess the performance of several forecasting methods by generating probabilistic technology cost forecasts rooted at various years in the past and then comparing these with observed costs in 2019. We do this for six technologies for which both observed and elicited data are available. The model-based methods use either deployment (Wright's law) or time (Moore's law) to forecast costs. We show that, overall, model-based forecasting methods outperformed elicitation methods. Their 2019 cost forecast ranges contained the observed values much more often than elicitations, and their forecast medians were closer to observed costs. However, all methods underestimated technological progress in almost all technologies, likely as a result of structural change across the energy sector due to widespread policies and social and market forces. We also produce forecasts of 2030 costs using the two types of methods for 10 energy technologies. We find that elicitations generally yield narrower uncertainty ranges than model-based methods. Model-based 2030 forecasts are lower for more modular technologies and higher for less modular ones. Future research should focus on further method development and validation to better reflect structural changes in the market and correlations across technologies. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Energy technology costs; Energy transition; Expert elicitation; Model-based technology forecasts; Uncertainty
语种	英语
scopus关键词	article; climate; forecasting; human; uncertainty; validation process
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/238493
作者单位	The Bartlett School of Sustainable Construction, University College London, London, WC1E 7HB, United Kingdom; Cambridge Centre for Environment, Energy and Natural Resource Governance, Department of Land Economy, University of Cambridge, Cambridge, CB3 9EP, United Kingdom; Institute for New Economic Thinking, The Oxford Martin School, University of Oxford, Oxford, OX1 3UQ, United Kingdom; Smith School of Enterprise and the Environment, University of Oxford, Oxford, OX1 3QY, United Kingdom; Department of Law, University of Brescia, Brescia, 25121, Italy; RFF-CMCC European Institute of Economics and the Environment, Euro-Mediterranean Center on Climate Change, Lecce, 73100, Italy; Belfer Center for Science and International Affairs, Harvard Kennedy School, Harvard University, Cambridge, MA 02138, United States
推荐引用方式 GB/T 7714	Meng J.,Way R.,Verdolini E.,et al. Comparing expert elicitation and model-based probabilistic technology cost forecasts for the energy transition[J],2021,118(27).
APA	Meng J.,Way R.,Verdolini E.,&Anadon L.D..(2021).Comparing expert elicitation and model-based probabilistic technology cost forecasts for the energy transition.Proceedings of the National Academy of Sciences of the United States of America,118(27).
MLA	Meng J.,et al."Comparing expert elicitation and model-based probabilistic technology cost forecasts for the energy transition".Proceedings of the National Academy of Sciences of the United States of America 118.27(2021).