Recommendations for a successful development of renewable energy communities based on the case studies of Austria and Denmark
Author
Prar, Ivona
Term
4. Term
Publication year
2023
Submitted on
2023-06-01
Pages
96
Abstract
Renewable energy communities (RECs) are local groups that produce and share energy from renewable sources. They can build support for clean technologies, reduce energy poverty through energy sharing, and cut greenhouse-gas emissions. The EU recognizes RECs in the Renewable Energy Directive (RED II) as part of the Clean Energy for All Europeans package. This thesis offers recommendations to help EU member states support the development of RECs. It draws on two case studies—Austria and Denmark—by examining how each country transposed RED II into national law and by interviewing community members to understand current conditions. The analysis also considers a Danish example of democratic innovation from the 1970s and a bottom-up approach that emphasizes citizen-led initiatives. The recommendations are organized for action at the EU, national, and local levels.
Vedvarende energifællesskaber (RECs) er lokale fællesskaber, der producerer og deler energi fra vedvarende kilder. De kan øge opbakningen til grøn teknologi, mindske energifattigdom ved at dele energi og reducere udledningen af drivhusgasser. EU anerkender RECs i det reviderede vedvarende energidirektiv (RED II) som en del af pakken Ren energi til alle europæere. Denne afhandling giver anbefalinger, der kan hjælpe EU-landene med at fremme RECs. Den bygger på to casestudier—Østrig og Danmark—ved at undersøge, hvordan hvert land har omsat RED II til national lovgivning, og ved at interviewe medlemmer af energifællesskaber om den nuværende situation. Analysen inddrager også et dansk eksempel på demokratisk innovation fra 1970’erne samt en bottom-up-tilgang, hvor initiativer starter hos borgere og lokalsamfund. Resultatet er et sæt anbefalinger opdelt i handlinger på EU-, nationalt og lokalt niveau.
[This apstract has been rewritten with the help of AI based on the project's original abstract]
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