Cost, resiliency and emissions trade-offs for microgrids in varying socioeconomic settings

Microgrids offer a decentralized approach to meeting energy and heating demands and can integrate renewable energy technologies, thereby facilitating emissions reductions. This study presents a mixed-integer nonlinear microgrid design and dispatch optimization model that incorporates load shedding. Although existing optimization models examine the trade-offs between meeting demand and the infrastructure and operational cost of doing so, this research contributes by determining the social cost (in terms of health impacts), particularly on vulnerable populations, of failing to supply power during outages, and the extent to which a microgrid can mitigate such outages, albeit at a financial cost. Using case studies across a diverse set of communities, the research examines the ramifications of power outages on healthcare devices. Our findings indicate that a failure to meet at least 20% of energy demand during outages can affect health device functionality, impacting 2%–7% of the population in higher vulnerability communities, compared to having negligible effects in non-vulnerable populations. Conversely, meeting at least 80% of demand during outages impacts less than 2% of the population in the affected community, although with an increase in cost of approximately 25%. Furthermore, the research analyzes changes in pollutant concentrations, attributing them to premature deaths. Employing a model that simulates point-source pollution, our microgrid model, with an emphasis on solid oxide fuel cells, achieves CO2 reductions of up to 5% relative to cases in which no emissions reductions are enforced, with minimal cost increase (typically around 1%). This reduction in emissions corresponds to a 4%–9% decrease in mortality rates.