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Energy R&D portfolio analysis based on climate change mitigation

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  • Pugh, Graham
  • Clarke, Leon
  • Marlay, Robert
  • Kyle, Page
  • Wise, Marshall
  • McJeon, Haewon
  • Chan, Gabriel

Abstract

The diverse nature and uncertain potential of the energy technologies that are or may be available to mitigate greenhouse gas emissions pose a challenge to policymakers trying to invest public funds in an optimal R&D portfolio. This paper discusses two analytical approaches to this challenge used to inform funding decisions related to the U.S. Department of Energy (DOE) applied energy R&D portfolio. The two approaches are distinguished by the constraints under which they were conducted: the need to provide an end-to-end portfolio analysis as input to internal DOE budgeting processes, but with limited time and subject to institutional constraints regarding important issues such as expert judgment. Because of these constraints, neither approach should be viewed as an attempt to push forward the state of the art in portfolio analysis in the abstract. Instead, they are an attempt to use more stylized, heuristic methods that can provide first-order insights in the DOE institutional context. Both approaches make use of advanced technology scenarios implemented in an integrated assessment modeling framework and then apply expert judgment regarding the likelihood of achieving associated R&D and commercialization goals. The approaches differ in the granularity of the scenarios used and in the definition of the benefits of technological advance: in one approach the benefits are defined as the cumulative emission reduction attributable to a particular technology; in the other approach benefits are defined as the cumulative cost reduction. In both approaches a return on investment (ROI) criterion is established based on benefits divided by federal R&D investment. The ROI is then used to build a first-order approximation of an optimal applied energy R&D investment portfolio. Although these methodologies have been used to inform an actual budget request, the results reflect only one input among many used in budget formulation. The results are therefore not representative of an official U.S. government or DOE funding recommendation but should instead be considered illustrative of the way in which methodologies such as these could be applied.

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  • Pugh, Graham & Clarke, Leon & Marlay, Robert & Kyle, Page & Wise, Marshall & McJeon, Haewon & Chan, Gabriel, 2011. "Energy R&D portfolio analysis based on climate change mitigation," Energy Economics, Elsevier, vol. 33(4), pages 634-643, July.
    • Handle: RePEc:eee:eneeco:v:33:y:2011:i:4:p:634-643
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    References listed on IDEAS

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    Cited by:

    1. Olaleye, Olaitan & Baker, Erin, 2015. "Large scale scenario analysis of future low carbon energy options," Energy Economics, Elsevier, vol. 49(C), pages 203-216.
    2. Mort Webster & Karen Fisher-Vanden & David Popp & Nidhi Santen, 2017. "Should We Give Up after Solyndra? Optimal Technology R&D Portfolios under Uncertainty," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(S1), pages 123-151.
    3. Brown, Marilyn A. & Gumerman, Etan & Sun, Xiaojing & Sercy, Kenneth & Kim, Gyungwon, 2012. "Myths and facts about electricity in the U.S. South," Energy Policy, Elsevier, vol. 40(C), pages 231-241.
    4. Gunnar Luderer & Volker Krey & Katherine Calvin & James Merrick & Silvana Mima & Robert Pietzcker & Jasper van Vliet & Kenichi Wada, 2014. "The role of renewable energy in climate stabilization: results from the EMF27 scenarios," Post-Print halshs-00961843, HAL.
    5. McJeon, Haewon C. & Clarke, Leon & Kyle, Page & Wise, Marshall & Hackbarth, Andrew & Bryant, Benjamin P. & Lempert, Robert J., 2011. "Technology interactions among low-carbon energy technologies: What can we learn from a large number of scenarios?," Energy Economics, Elsevier, vol. 33(4), pages 619-631, July.
    6. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2017. "Inter-temporal R&D and capital investment portfolios for the electricity industrys low carbon future," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    7. Rob Aalbers & Victoria Shestalova & Viktoria Kocsis, 2012. "Innovation policy for directing technical change in the power sector," CPB Discussion Paper 223, CPB Netherlands Bureau for Economic Policy Analysis.
    8. Aalbers, Rob & Shestalova, Victoria & Kocsis, Viktória, 2013. "Innovation policy for directing technical change in the power sector," Energy Policy, Elsevier, vol. 63(C), pages 1240-1250.
    9. Milford, James & Henrion, Max & Hunter, Chad & Newes, Emily & Hughes, Caroline & Baldwin, Samuel F., 2022. "Energy sector portfolio analysis with uncertainty," Applied Energy, Elsevier, vol. 306(PA).
    10. Diaz Anadon, Laura & Bosetti, Valentina & Chan, Gabriel & Nemet, Gregory & Verdolini, Elena, 2014. "Energy Technology Expert Elicitations for Policy: Workshops, Modeling, and Meta-analysis," Working Paper Series rwp14-054, Harvard University, John F. Kennedy School of Government.
    11. Shi, Wenjing & Ou, Yang & Smith, Steven J. & Ledna, Catherine M. & Nolte, Christopher G. & Loughlin, Daniel H., 2017. "Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA," Applied Energy, Elsevier, vol. 208(C), pages 511-521.
    12. Jasper Vliet & Andries Hof & Angelica Mendoza Beltran & Maarten Berg & Sebastiaan Deetman & Michel Elzen & Paul Lucas & Detlef Vuuren, 2014. "The impact of technology availability on the timing and costs of emission reductions for achieving long-term climate targets," Climatic Change, Springer, vol. 123(3), pages 559-569, April.
    13. Forouli, Aikaterini & Doukas, Haris & Nikas, Alexandros & Sampedro, Jon & Van de Ven, Dirk-Jan, 2019. "Identifying optimal technological portfolios for European power generation towards climate change mitigation: A robust portfolio analysis approach," Utilities Policy, Elsevier, vol. 57(C), pages 33-42.
    14. Ashina, Shuichi & Fujino, Junichi & Masui, Toshihiko & Ehara, Tomoki & Hibino, Go, 2012. "A roadmap towards a low-carbon society in Japan using backcasting methodology: Feasible pathways for achieving an 80% reduction in CO2 emissions by 2050," Energy Policy, Elsevier, vol. 41(C), pages 584-598.
    15. Kurth, Margaret & Keisler, Jeffrey M. & Bates, Matthew E. & Bridges, Todd S. & Summers, Jeffrey & Linkov, Igor, 2017. "A portfolio decision analysis approach to support energy research and development resource allocation," Energy Policy, Elsevier, vol. 105(C), pages 128-135.
    16. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2014. "Inter-temporal R&D and Capital Investment Portfolios for the Electricity Industry's Low Carbon Future," CESifo Working Paper Series 5139, CESifo.
    17. Gunnar Luderer & Volker Krey & Katherine Calvin & James Merrick & Silvana Mima & Robert Pietzcker & Jasper Vliet & Kenichi Wada, 2014. "The role of renewable energy in climate stabilization: results from the EMF27 scenarios," Climatic Change, Springer, vol. 123(3), pages 427-441, April.
    18. Haris Doukas & Alexandros Nikas & Mikel González-Eguino & Iñaki Arto & Annela Anger-Kraavi, 2018. "From Integrated to Integrative: Delivering on the Paris Agreement," Sustainability, MDPI, vol. 10(7), pages 1-10, July.
    19. Nidhi R. Santen & Mort D. Webster & David Popp & Ignacio Pérez-Arriaga, 2014. "Inter-temporal R&D and Capital Investment Portfolios for the Electricity Industry’s Low Carbon Future," NBER Working Papers 20783, National Bureau of Economic Research, Inc.
    20. Sang Jin Choi & Dong Gu Choi & Paul Friley & Hyunkeong Kim & Sang Yong Park, 2017. "Quantitative Analysis on the Energy and Environmental Impact of the Korean National Energy R&D Roadmap a Using Bottom-Up Energy System Model," Sustainability, MDPI, vol. 9(4), pages 1-20, March.

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