Sustainability of community-owned mini-grids: Evidence from India

Background: Community-owned solar mini-grids (SMGs) are increasingly promoted to provide communities access to reliable electricity, empowering local actors as they become active stakeholders in projects. However, early failures and difficulties in building local capacity have raised questions regarding their long-term sustainability and ability to be replicated to provide socio-economic benefits to the communities. This study assesses the sustainability of 24 community-owned SMGs in India operating over extensive periods of time using a novel scoring framework using mixed methods to derive its conclusions. Results: The study found that institutional, financial, and technical capacities, central for the SMG's long-term sustainability, could be achieved through community engagement from early stages, if communities are allowed freedom to develop governance procedures while at the same time clarifying roles and responsibilities. This creates strong sense of ownership that is key for effective and inclusive governance. User satisfaction, ensured through provision of usable supply in line with users' expectations, motivates actors to make regular payments, thus leading to economic sustenance. While social and environmental benefits were observed, energy consumption and engagement in productive activities remained marginal. Conclusions: The study reports an example of community-owned SMG model that has been replicated sustainably over many cases, overcoming key challenges related to appropriate financial and technical management and producing positive social impact. Low engagement in productive activities was more a factor of the local socio-cultural contexts, rather than limited paying capacities of the users. To increase energy utilization and create environments for sustainable rural living, the study recommends implementation of systems that link energy with other rural development needs such as agriculture or water provision. The study also recommends more use of qualitative and quantitative data for impact analysis to ensure that conclusions are generalizable and provide rich contextual explanations for the observed phenomena.