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Abstract This perspective explores the imperative role of participatory research (PR) in advancing energy justice. We argue that using PR methods and principles at the intersection of energy and equity is a critical research advantage. Here, we contend that PR frameworks are integral to bridging the gap between energy justice theory and practice, emphasizing the need to move beyond decontextualized principles to address specific injustices related to race, class, gender, and coloniality. We present three energy justice case studies that used participatory approaches in diverse contexts: Amazon, Brazil; Philadelphia, Pennsylvania, USA; and Holyoke, Massachusetts, USA. These cases showcase the versatility of PR methods in understanding and addressing unique energy challenges within local communities. We highlight guiding principles of PR, emphasizing the importance of prioritizing community needs, respecting diverse expertise, building trust, designing for transparency and accountability, choosing appropriate methods, adapting and being flexible, and aiming for long-term collaboration. Lastly, our perspective suggests future directions for participatory energy justice research, including the potential for PR to inform multiscalar policy, practice, and advocacy. We underscore the importance of collaborations between university researchers and community organizations through citizen science, emphasizing the need for diverse disciplinary perspectives to effectively address complex energy justice challenges. 

Millions of people across the world live off-grid not by choice but because they live in rural areas, have low income, and have no political clout. Delivering sustainable energy solutions to such a substantial amount of the world’s population requires more than a technological fix; it requires leveraging the knowledge of underserved populations working together with a transdisciplinary team to find holistically derived solutions. Our original research has resulted in an innovative Convergence Framework integrating the fields of engineering, social sciences, and communication, and is based on working together with communities and other stakeholders to address the challenges posed by delivering clean energy solutions. In this paper, we discuss the evolution of this Framework and illustrate how this Framework is being operationalized in our on-going research project, cocreating hybrid renewable energy systems for off-grid communities in the Brazilian Amazon. The research shows how this Framework can address clean energy transitions, strengthen emerging industries at local level, and foster Global North–South scholarly collaborations. We do so by the integration of social science and engineering and by focusing on community engagement, energy justice, and governance for underserved communities. Further, this solution-driven Framework leads to the emergence of unique approaches that advance scientific knowledge, while at the same time addressing community needs. 

Abstract While there have been efforts to supply off-grid energy in the Amazon, these attempts have focused on low upfront costs and deployment rates. These “get-energy-quick” methods have almost solely adopted diesel generators, ignoring the environmental and social risks associated with the known noise and pollution of combustion engines. Alternatively, it is recommended, herein, to supply off-grid needs with renewable, distributed microgrids comprised of photovoltaics (PV) and in-stream generators (ISG). Utilization of a hybrid combination of renewable generators can provide an energetically, environmentally, and financially feasible alternative to typical electrification methods, depending on available solar irradiation and riverine characteristics, that with community engagement allows for a participatory codesign process that takes into consideration people’s needs. A convergent solution development framework that includes designers—a team of social scientists, engineers, and communication specialists—and communities as well as the local industry is examined here, by which the future negative impacts at the human–machine–environment nexus can be minimized by iterative, continuous interaction between these key actors.