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A portfolio decision analysis approach to support energy research and development resource allocation

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  • Kurth, Margaret
  • Keisler, Jeffrey M.
  • Bates, Matthew E.
  • Bridges, Todd S.
  • Summers, Jeffrey
  • Linkov, Igor

Abstract

Research sponsored by the US Department of Energy (DOE) aims to facilitate a clean and independent energy future for the nation. Strategic planning for energy research and development (R&D) can be complex and dynamic, in part due to federal budgetary constraints and volatility. Managing R&D funding to advance energy technologies, in spite of these challenges, is a crucial component of the nation's long term energy policy. This study demonstrates a portfolio decision analysis (PDA) approach to support R&D resource allocation decisions for the DOE Office of Fossil Energy's Carbon Capture and Storage R&D program. A multi-attribute value model uses technology readiness levels (TRLs) and other metrics to represent the overall objectives of the R&D program in order to evaluate alternative research portfolios given limited funding. Mathematical optimization identifies efficient funding allocations for each technology program area to maximize the multi-attribute value generated from the total budget. This is especially useful for responding to externally imposed budget changes. As the case study demonstrates, explicitly funding the most value-generating options leads to greater expected R&D programmatic value than typical strategies of equal or proportional distributions of a budget change among technology program areas.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:enepol:v:105:y:2017:i:c:p:128-135
    DOI: 10.1016/j.enpol.2017.02.030
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    References listed on IDEAS

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    4. Mavrotas, George & Makryvelios, Evangelos, 2021. "Combining multiple criteria analysis, mathematical programming and Monte Carlo simulation to tackle uncertainty in Research and Development project portfolio selection: A case study from Greece," European Journal of Operational Research, Elsevier, vol. 291(2), pages 794-806.
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