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Investing in Smart Grids: Assessing the Influence of Regulatory and Market Factors on Investment Level

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  • Yvonne Vogt Gwerder
  • Nuno Carvalho Figueiredo
  • Patrícia Pereira da Silva

Abstract

This paper explores how market and regulatory factors affect stakeholders' investments in smart grid projects in Europe. Distribution System Operators (DSOs), universities, and technology manufacturers are leading investors, with a cumulative 2286 M€ financed since 2002. Statistical tests were conducted on these groups' investments in smart grid projects in the EU-28, Norway, and Switzerland from 2008-2015, to evaluate the influence of the following factors on investment: the level of distribution sector concentration, the regulatory mechanism in place, and the existence of innovation stimulus mechanisms. The level of distribution sector concentration did not significantly influence investments by these three groups. Market-minded stakeholders, such as DSOs and technology manufacturers, invested more in countries that employed hybrid, incentive, or innovation-stimulus mechanisms; meanwhile, collaborative knowledge-seeking institutions, such as universities, were not swayed by these factors. Taking these findings into consideration will help policy makers design adequate incentives for stakeholders.

Suggested Citation

  • Yvonne Vogt Gwerder & Nuno Carvalho Figueiredo & Patrícia Pereira da Silva, 2019. "Investing in Smart Grids: Assessing the Influence of Regulatory and Market Factors on Investment Level," The Energy Journal, , vol. 40(4), pages 25-44, July.
  • Handle: RePEc:sae:enejou:v:40:y:2019:i:4:p:25-44
    DOI: 10.5547/01956574.40.4.ygwe
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    References listed on IDEAS

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    2. Guillermo Ivan Pereira & Patrícia Pereira Silva & Deborah Soule, 2018. "Policy-adaptation for a smarter and more sustainable EU electricity distribution industry: a foresight analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(1), pages 231-267, December.
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    Cited by:

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    2. Kingsley Ukoba & Kehinde O. Olatunji & Eyitayo Adeoye & Tien-Chien Jen & Daniel M. Madyira, 2024. "Optimizing renewable energy systems through artificial intelligence: Review and future prospects," Energy & Environment, , vol. 35(7), pages 3833-3879, November.

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