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Energy management under policy and technology uncertainty

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  • Tylock, Steven M.
  • Seager, Thomas P.
  • Snell, Jeff
  • Bennett, Erin R.
  • Sweet, Don

Abstract

Energy managers in public agencies are subject to multiple and sometimes conflicting policy objectives regarding cost, environmental, and security concerns associated with alternative energy technologies. Making infrastructure investment decisions requires balancing different distributions of risks and benefits that are far from clear. For example, managers at permanent Army installations must incorporate Congressional legislative objectives, executive orders, Department of Defense directives, state laws and regulations, local restrictions, and multiple stakeholder concerns when undertaking new energy initiatives. Moreover, uncertainty with regard to alternative energy technologies is typically much greater than that associated with traditional technologies, both because the technologies themselves are continuously evolving and because the intermittent nature of many renewable technologies makes a certain level of uncertainty irreducible. This paper describes a novel stochastic multi-attribute analytic approach that allows users to explore different priorities or weighting schemes in combination with uncertainties related to technology performance. To illustrate the utility of this approach for understanding conflicting policy or stakeholder perspectives, prioritizing the need for more information, and making investment decisions, we apply this approach to an energy technology decision problem representative of a permanent military base.

Suggested Citation

  • Tylock, Steven M. & Seager, Thomas P. & Snell, Jeff & Bennett, Erin R. & Sweet, Don, 2012. "Energy management under policy and technology uncertainty," Energy Policy, Elsevier, vol. 47(C), pages 156-163.
  • Handle: RePEc:eee:enepol:v:47:y:2012:i:c:p:156-163
    DOI: 10.1016/j.enpol.2012.04.040
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    References listed on IDEAS

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    Cited by:

    1. Haichao Wang & Wenling Jiao & Risto Lahdelma & Chuanzhi Zhu & Pinghua Zou, 2014. "Stochastic Multicriteria Acceptability Analysis for Evaluation of Combined Heat and Power Units," Energies, MDPI, vol. 8(1), pages 1-20, December.
    2. R. Pelissari & M. C. Oliveira & S. Ben Amor & A. Kandakoglu & A. L. Helleno, 2020. "SMAA methods and their applications: a literature review and future research directions," Annals of Operations Research, Springer, vol. 293(2), pages 433-493, October.
    3. Kostevšek, Anja & Petek, Janez & Čuček, Lidija & Pivec, Aleksandra, 2013. "Conceptual design of a municipal energy and environmental system as an efficient basis for advanced energy planning," Energy, Elsevier, vol. 60(C), pages 148-158.
    4. Z. A. Collier & D. Wang & J. T. Vogel & E. K. Tatham & I. Linkov, 2013. "Sustainable roofing technology under multiple constraints: a decision-analytical approach," Environment Systems and Decisions, Springer, vol. 33(2), pages 261-271, June.
    5. Dassisti, M. & Carnimeo, L., 2013. "A small-world methodology of analysis of interchange energy-networks: The European behaviour in the economical crisis," Energy Policy, Elsevier, vol. 63(C), pages 887-899.
    6. Silvia Angilella & Maria Rosaria Pappalardo, 2022. "Performance assessment of energy companies employing Hierarchy Stochastic Multi-Attribute Acceptability Analysis," Operational Research, Springer, vol. 22(1), pages 299-370, March.
    7. Hamilton, Michelle C. & Lambert, James H. & Connelly, Elizabeth B. & Barker, Kash, 2016. "Resilience analytics with disruption of preferences and lifecycle cost analysis for energy microgrids," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 11-21.
    8. Donald J. Jenkins & Jeffrey M. Keisler, 2022. "A decision analytic tool for corporate strategic sustainable energy purchases," Environment Systems and Decisions, Springer, vol. 42(4), pages 504-520, December.
    9. Shekarchian, M. & Moghavvemi, M. & Zarifi, F. & Moghavvemi, S. & Motasemi, F. & Mahlia, T.M.I., 2017. "Impact of infrastructural policies to reduce travel time expenditure of car users with significant reductions in energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 327-335.

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    Keywords

    MCDA; Uncertainty; Stakeholders;
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