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Impacts of Decentralized Power Generation on Distribution Networks: a Statistical Typology of European Countries

Authors :
Frédéric Gonand
Marie Bessec
Darius Corbier
Centre de Géopolitique de l’Energie et des Matières Premières (LEDA-CGEMP)
Laboratoire d'Economie de Dauphine (LEDa)
Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Paris Dauphine-PSL
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Paris Dauphine-PSL
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
Université Paris Dauphine-PSL
Institut de Recherche pour le Développement (IRD)-Université Paris Dauphine-PSL-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Paris Dauphine-PSL-Centre National de la Recherche Scientifique (CNRS)
Source :
Environmental Modeling & Assessment, Environmental Modeling & Assessment, Springer, 2018, 23 (5), ⟨10.1007/s10666-018-9621-7⟩
Publication Year :
2018
Publisher :
Springer Science and Business Media LLC, 2018.

Abstract

The development of decentralized sources of power out of renewable sources of energies has been triggering far-reaching consequences for Distribution System Operators over the past decade in Europe. Our paper benchmarks across 23 European countries the impact of the development of renewables on the physical characteristics of power distribution networks and on their investments. It builds on a large spectrum of databases of quantitative indicators about the dynamics of installed capacity of renewable energy resources and the power generation out of them, electricity independence, quality of electricity distribution, smart grids investments, Network System Operators capital expenditures, length of the distribution networks, overall costs of power networks paid by private agents, and electricity losses, all in relation with the development of decentralized generation. The heterogeneity of these indicators across Europe appears to be wide notably because of physical constraints, historic legacies, or policy and regulatory choices. A cluster analysis allows for deriving six groups of countries that display statistically homogenous characteristics. Our results may provide decision makers and regulators with a tool helping them to concentrate on the main issues specific to their countries as compared to the European median, and to look for possible solutions in the experience of other clusters which are shown to perform better for some indicators.

Details

ISSN :
15732967 and 14202026
Volume :
23
Database :
OpenAIRE
Journal :
Environmental Modeling & Assessment
Accession number :
edsair.doi.dedup.....eb62b8dded98c16e0d2d875e75f8575f