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The salience and complexity of building, regulating, and governing the smart grid: Lessons from a statewide public–private partnership


  • Koliba, Christopher
  • DeMenno, Mercy
  • Brune, Nancy
  • Zia, Asim


Smart grid deployment unfolds within a diverse array of multi-institutional arrangements that may be too fragmented and decentralized to allow for the kind of large-scale and coordinated investments needed to properly deploy the smart grid. This case study provides an account of how one state arranged for and eventually deployed smart grid technology to over 85 percent of its resident. The study asks: does the deployment of the smart grid introduce new socio-political variables into the electricity distribution industry? To make sense of the socio-political variables shaping the industry and regulators, the Salience–Complexity Model is used to assess whether the smart grid raises or lowers the level of public scrutiny caste upon the industry (issue salience) and the level of technical capacity needed to execute and utilize the smart grid (technical complexity). The conclusions to be drawn from this study include: smart grid technology heightens the issue salience and the technical complexity of electricity distribution, but that the smart grid will likely not have a significant impact on the restructuring of electricity regulation.

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  • Koliba, Christopher & DeMenno, Mercy & Brune, Nancy & Zia, Asim, 2014. "The salience and complexity of building, regulating, and governing the smart grid: Lessons from a statewide public–private partnership," Energy Policy, Elsevier, vol. 74(C), pages 243-252.
  • Handle: RePEc:eee:enepol:v:74:y:2014:i:c:p:243-252
    DOI: 10.1016/j.enpol.2014.09.013

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    References listed on IDEAS

    1. McHenry, Mark P., 2013. "Technical and governance considerations for advanced metering infrastructure/smart meters: Technology, security, uncertainty, costs, benefits, and risks," Energy Policy, Elsevier, vol. 59(C), pages 834-842.
    2. Agrell, Per J. & Bogetoft, Peter & Mikkers, Misja, 2013. "Smart-grid investments, regulation and organization," Energy Policy, Elsevier, vol. 52(C), pages 656-666.
    3. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
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    Cited by:

    1. Aurelie Tricoire, 2015. "Uncertainty, vision, and the vitality of the emerging smart grid," Post-Print hal-02351994, HAL.
    2. Lee, Taedong & Glick, Mark B. & Lee, Jae-Hyup, 2020. "Island energy transition: Assessing Hawaii's multi-level, policy-driven approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    3. Rodrigues, E.M.G. & Osório, G.J. & Godina, R. & Bizuayehu, A.W. & Lujano-Rojas, J.M. & Catalão, J.P.S., 2016. "Grid code reinforcements for deeper renewable generation in insular energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 163-177.
    4. Jelena Lukić & Miloš Radenković & Marijana Despotović-Zrakić & Aleksandra Labus & Zorica Bogdanović, 2017. "Supply chain intelligence for electricity markets: A smart grid perspective," Information Systems Frontiers, Springer, vol. 19(1), pages 91-107, February.

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