Trade-Offs in Justice-Oriented Grid Expansions

Changing infrastructure to meet the energy needs of an increasingly electrified, lower-carbon future provides an opportunity to address historically localized impacts or disproportionate burdens. In this work, we study the effects of five justice-oriented policy preferences to guide the evolution and expansion of a portion of the U.S. electricity grid. We develop and implement a scenario-based framework with a Mixed Integer Linear Programming model to identify cost-minimizing electricity generation siting at the county level that follows specific grid expansion projections in the PJM West region. We compare the costs, job creation, and CO2,eq emissions from portfolios guided by justice-oriented policies with those of the least-cost electricity grid – focusing on counties with low-resilience to job losses from ongoing fossil fuel transitions. We find that strategies that minimize financial costs do not incentivize deployment in low-resilience counties, yet the results of the most expensive justice-oriented scenario that invests in those counties is only 0.7% more costly than the simple, cost minimizing approach. We further identify trade-offs between costs and emissions across several aspects of sustainability and justice. The results support the notion that policy design should consider social and environmental impacts in addition to costs, rather than pursuing these goals in isolation. Article co-authors are Daniel Gingerich (Assistant Professor at the College of Engineering at The Ohio State University) and Kelsea Best (Assistant Professor at the College of Engineering and Knowlton School of Architecture at The Ohio State University).