Growing community energy initiatives from the bottom up: Simulating the role of behavioural attitudes and leadership in the Netherlands

Amineh Ghorbani*, Leonardo Nascimento, Tatiana Filatova

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

30 Citations (Scopus)
50 Downloads (Pure)

Abstract

Local energy initiatives (LEIs) are communities of households who self-organize to meet their energy demand with locally produced green energy. They facilitate citizen participation by developing context-specific solutions, which calls for leadership and complex social dynamics. We present an agent-based simulation model to explore the formation of community energy initiatives from the bottom-up, accounting for social networks and evolution of opinions facilitating or hindering LEIs. Our novel model relies on well-established social theories and uses empirical data on community energy systems in the Netherlands and individual citizens’ preferences. Specifically, our computational model captures behavioural drivers and social value orientations, and relates individuals behavioural traits to aggregated stylized facts about energy initiatives at the community level. The results indicate that when communities lack participants with cooperative orientation, altruistic citizens with prosocial social value orientations become essential for the creation of LEIs, revealing different pathways to achieve public good benefits. Our analysis systematically demonstrate that leaders can be a bottleneck in the LEIs’ formation and that an increase in initiators is conducive to the creation of LEIs. Therefore, policies aiming at increasing the number of community initiatives should target small groups and individuals with the leadership potential, who could lead projects, and explore synergies with wider community benefits.

Original languageEnglish
Article number101782
JournalEnergy Research and Social Science
Volume70
DOIs
Publication statusPublished - 2020

Keywords

  • Agent-based modelling
  • Collective action
  • Community energy systems
  • Leadership
  • Local energy initiatives
  • Solar
  • Wind energy

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