Abstract
Governments are dealing with the challenge of how to efficiently invest in research and development portfolios related to energy technologies. Research and development investment decisions in the energy space are especially difficult due to numerous risks and uncertainties, and due to the complexity of energy's interactions with the broad economy. Historically, much of the U.S. Department of Energy's in-depth research and development analyses focused on assessing the impact of a research and development activity in isolation from other available opportunities and did not substantially consider risk and uncertainty. Endeavoring to combine integrated energy-economy modeling with uncertainty analysis and technology-specific research and development activities, the U.S. Department of Energy commissioned the development of the Stochastic Energy Deployment System to support and improve public energy research and development decision-making. The Stochastic Energy Deployment System draws from expert-elicited probability distributions for research and development-driven improvements in technology cost and performance, and it uses Monte Carlo simulations to evaluate the likelihood of outcomes within a system dynamics energy-economy model. The framework estimates the uncertain benefits and costs of various research and development portfolios and provides insight into the probability of meeting national technology goals, while accounting for interactions with the larger economy and for interactions among research and development investments spanning many energy sectors.
Original language | American English |
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Article number | 117926 |
Number of pages | 14 |
Journal | Applied Energy |
Volume | 306 |
Issue number | Part A |
DOIs | |
State | Published - 2022 |
Bibliographical note
Publisher Copyright:© 2021 The Authors
NREL Publication Number
- NREL/JA-6A20-78746
Keywords
- Energy system
- Expert elicitation
- Portfolio analysis
- Stochastic Energy Deployment System
- Stochasticity
- Uncertainty