Trust, awareness, and independence

Trust, awareness, and independence: Insights from a socio-psychological factor analysis of citizen knowledge and participation in community energy systems

Koirala, B.P. (TU Delft Energie and Industrie; University of Twente)
Araghi, Y. (TU Delft Energie and Industrie)
Kroesen, M. (TU Delft Transport and Logistics)
Ghorbani, Amineh (TU Delft Energie and Industrie)
Hakvoort, R.A. (TU Delft Energie and Industrie)
Herder, P.M. (TU Delft Energie and Industrie)

2018

In order to decarbonize the energy sector, there is a widespread consensus that the role of end-users in the energy system should change from passive consumption to active prosumption and engagement. This is of particular importance as an increasing number of technologies and business models are focusing on the end-users. These developments provide new opportunities for further technical and social innovation to smarter, flexible and integrated systems such as community energy systems (CESs). Through system integration and community engagement CESs assist in transition to a low-carbon energy system. Despite the high importance, there is limited knowledge on willingness of local citizens to participate in the local energy systems such as CESs as well as associated factors determining such willingness. Through a survey among 599 citizens in the Netherlands, this research analyses the impact of demographic, socio-economic, socio-institutional as well as environmental factors on willingness to participate in CESs. Factor and multi-variate regression analysis reveals that the environmental concern, renewables acceptance, energy independence, community trust, community resistance, education, energy related education and awareness about local energy initiatives are the most important factors in determining the citizens’ willingness to participate in CESs. Citizens should be empowered to take active role in steering the local energy initiatives.

Citizen participation
Distributed energy resources
Energy communities
Energy transition
Factor analysis
Multi-variate regression analysis

http://resolver.tudelft.nl/uuid:5d765b9a-88ad-43f4-8b30-fe329779987f

https://doi.org/10.1016/j.erss.2018.01.009

2214-6296

Energy Research and Social Science, 38, 33-40

Institutional Repository

journal article

© 2018 B.P. Koirala, Y. Araghi, M. Kroesen, Amineh Ghorbani, R.A. Hakvoort, P.M. Herder