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  4. Analysing the potential of citizen-financed community renewable energy to drive Europe's low-carbon energy transition
 
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Analysing the potential of citizen-financed community renewable energy to drive Europe's low-carbon energy transition

Journal
Renewable and Sustainable Energy Reviews
ISSN
1364-0321
Type
journal article
Date Issued
2020-08-28
Author(s)
Pons-Seres de Brauwer, Cristian  
Cohen, Jed J.
DOI
https://doi.org/10.1016/j.rser.2020.110300
Abstract
In 2018, the real amount invested in the European Union's energy transition fell short of the funding level required to reach the 2030 climate and energy targets by €179 billion. Citizen-led finance in renewable energy development emerges as an innovative tool to bridge this investment gap. However, in spite of the European Union's ambition to involve local communities for co-driving the low-carbon energy transition, there is no comprehensive analysis quantifying citizens' potential to co-finance and participate in community renewable energy initiatives across Europe. We address this knowledge gap through a representative choice experiment survey that collected responses from 16,235 participants to different hypothetical investment options on renewable energy schemes across all European Union Member States, and estimate the social potential of European citizens to participate and invest in community-administered wind farms. Results from a novel survey-based social simulation indicate that €176 billion could be obtained from citizen-led finance in community-administered wind farm developments, enough to halve the investment gap to achieve a 32% renewable energy share in final energy consumption by 2030. Our analysis substantiates the case for facilitating easily accessible, risk-insured community investment options across Europe to unlock citizens' social potential for investing in community renewable energy.
Funding(s)
MISTRAL-ITN
ECHOES
Language
English
Keywords
Community renewable energy
Social potential
Energy transition
Citizen finance
Survey-based social simulation
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Elsevier
Volume
133
Number
110300
Pages
12
Official URL
https://www.sciencedirect.com/science/article/pii/S1364032120305888?via%3Dihub
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/111846
Subject(s)

other research area

econometrics

social sciences

behavioral science

Contact Email Address
cristian.debrauwer@unisg.ch
Eprints ID
269236
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