A central challenge for energy policy is to simultaneously accelerate the transition to carbon neutrality to tackle climate change while also addressing diverse forms of energy inequality and injustice. In this article, we argue that the public imagination is central to efforts to successfully confront this dual challenge. Specifically, we argue that theories of sociotechnical imaginaries have the potential to be leveraged both to strengthen public support for and engagement in carbon-neutral energy transitions and to identify and catalyze integrated sociotechnical designs and solutions that deliver on both accelerated technological change and just, equitable, and inclusive transitions. To explore these ideas, we present an in-depth case study of an emergent sociotechnical imaginary surrounding solar energy technologies in Puerto Rico. The results of our case study suggest that new imaginaries have the potential both to create powerful public support for renewable energy technologies that can accelerate energy systems change and, at the same time, help illuminate strategies for deploying energy technologies in ways that create meaningful impact and value in people’s lives in diverse communities and thus contribute to making energy transitions more just and inclusive.

Access to electric energy is one of the drivers of wellbeing and universal access to energy has recently been identified as an important goal in the international community. A data-driven analysis of electric energy consumption and subjective wellbeing indicators is introduced to promote a broad conversation about relationships between energy poverty, global equity, subjective wellbeing measurements and good quality of life. The proposed approach directly focuses on the overall goal of attaining good and long lasting lives, the implications for future generations, the importance of ecosystems in enabling sustainable wellbeing and the needed capabilities in communities to flourish. Eventually, the proposed pathway should lead to a capabilities approach assessment for appropriate technologies. The results point out that although there is an important relationship between electric energy consumption and human wellbeing, a deeper look at electric energy access, subjective wellbeing indicators, local capabilities, and participatory decision making processes is needed to better prepare and implement long-term energy plans at local and global levels.

There has been an effort for a few decades to keep energy consumption at a minimum or at least within a low-level range. This effort is more meaningful and complex by including a customer’s satisfaction variable to ensure that customers can achieve the best quality of life that could be derived from how energy is used by different devices. We use the concept of Shapley Value from cooperative game theory to solve the multi-objective optimization problem (MOO) to responsibly fulfill user’s satisfaction by maximizing satisfaction while minimizing the power consumption, with energy constrains since highly limited resources scenarios are studied. The novel method uses the concept of a quantifiable user satisfaction, along the concepts of power satisfaction (PS) and energy satisfaction (ES). The model is being validated by representing a single house (with a small PV system) that is connected to the utility grid. The main objectives are to (i) present the innovative energy satisfaction model based on responsible wellbeing, (ii) demonstrate its implementation using a Shapley-value-based algorithm, and (iii) include the impact of a solar photovoltaic (PV) system in the energy satisfaction model. The proposed technique determines in which hours the energy should be allocated to maximize the ES for each scenario, and then it is compared to cases in which devices are usually operated. Through the proposed technique, the energy consumption was reduced 75% and the ES increased 40% under the energy constraints.

In order to achieve the objective of universal electricity access by 2030, new microgrids need to serve 630 million people globally. To achieve this goal, new finance models need to be developed and implemented. Load profiles of rural consumers are crucial for off-grid systems capacity planning and control. The combination of detailed load profiles with benefit assessment of rural electricity can provide important insights into the social dynamics of communities ready to adopt microgrid technologies and an important incentive to guide demand side management. We propose a Load Profile - Benefit Assessment (LPBA) methodology that integrates microgrid data, analyzed through mean shift clustering clustering technique, with mixed method instrumentation to adequately assess the impact electricity use has on consumers. Enabled by wellbeing assessment methodology, LPBA could change the perceived investment risk by taking a deeper look at the reasons why a rural electrification business succeeds or fails. Preliminary data from a case study of a rural secondary school in Tanzania is used here to illustrate the methodology. While microgrids connected to a reliable grid seek to reduce cost or maximize the hours of power output when the price per kWh is higher, the LPBA provides a general guideline for microgrid users to manage power consumption with the goal of maximizing wellbeing benefits. Initial results indicate that in order to scale up methodologies such as LPBA, innovation is needed in affordable smart meters, near-real time signal processing tools, and transactive energy appropriate technology.