Evaluating the impact of government energy R&D investments through a multi-attribute utility-based decision tool

Abstract

Government agencies characteristically face dynamic policy and investment environments yet frequently rely on ad-hoc decision-making methods in response to complexities inherent in their operating landscape. Additionally, standard decision making methods typically undervalue projects by ignoring difficult to value, non-monetary benefits. This presents a problem for public institutions, such as the Department of Energy (DOE), where goals relating to the environment and national security are difficult to quantify. As a result, it is especially challenging to accurately optimize the use of public funds. The Department of Energy (DOE) is responsible for making significant investment decisions under extreme uncertainty with respect to the nation's public energy portfolio. Recently, leaders internal and external to the government have called for a comprehensive and structured approach to assess the DOE's portfolio of programs and initiatives (PCAST, 2010), (American Energy Innovation Council, 2011). Given the broad spectrum of the DOE's current portfolio, from basic R&D to demonstration and across every major energy technology, evaluating the impacts of its potential investments is complex. Within the Department of Energy's Planning Analysis and Evaluation (PA&E) team, a proposal was made to develop a first-of-a-kind decision tool that would provide rigorous analysis of cost and benefit trade-offs associated with the DOE's investments. The decision tool was designed to couple a state-of-the-art climate and energy model with sophisticated multi-attribute-based decision methods. The research described in this thesis illuminates the advantages and shortcomings of the initial decision tool structure, and presents a second generation model that is tailored to the DOE's operational context. Finally, in order to expand its use for long-range strategy formation, an evolution of this second generation model is explored through the application of recent theoretical methodologies. The resulting decision tool is intended to play an informative role within a comprehensive portfolio review by enabling the enumeration of budgetary trade-offs that address high-level, strategy questions facing the DOE.