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As electric power grid critical infrastructure grows increasingly heterogeneous, a key question is how to encourage and ensure relatively equitable access to the energy it supplies. With diverse socio-economic regions linked to the grid and various generation types, achieving equitable access to clean energy, as outlined in initiatives like DOE’s Justice40, remains an important aspirational goal. Building on previous work, this paper describes our investigation of a heterogenous grid modeled on the Alaska Railbelt, allowing us to explore the intrinsic inequities and possible mechanisms to enhance the equity across regions. We apply risk and equity metrics to different regions to examine how penalties which change the cost can impact the equity as well as the overall grid’s risk and dynamics. 

As electric power grid critical infrastructure grows increasingly heterogeneous, a key question is how to encourage and ensure relatively equitable access to the energy it supplies. With diverse socio-economic regions linked to the grid and various generation types, achieving equitable access to clean energy, as outlined in initiatives like DOE’s Justice40, remains an important aspirational goal. Building on previous work, this paper describes our investigation of a heterogenous grid modeled on the Alaska Railbelt, allowing us to explore the intrinsic inequities and possible mechanisms to enhance the equity across regions. We apply risk and equity metrics to different regions to examine how penalties which change the cost can impact the equity as well as the overall grid’s risk and dynamics. 

In response to the expanding role of wind, solar, and storage, increasing demand flexibility, and a changing climate, new analytical methods and metrics to assess resource adequacy are needed. A focus has been on identifying ways to reduce risks of failure. Less attention has been directed to how new analytical approaches can inform the design of planning processes, regulatory standards, and markets. Using mixed methods and a community-engaged approach, data on community preferences and uneven distributions of impacts are used in a demonstration of a coupled socio-technical systems model that has been validated in diverse settings. The research is informed by the physical and institutional infrastructures in the Railbelt power grid of Alaska. The findings illustrate how new analytical tools can inform institutional design and facilitate more affordable, sustainable, and equitable outcomes. 

Natural gas network is important for residential heating, industrial manufacturing, and electricity generation. Although it is reliable and resilient to local disruptions, extreme situations such as natural disasters and political conflicts can degenerate its capability of gas transportation and delivery, influencing other social activities. Evaluating loadability regions of natural gas networks is hard due to nonlinear constraints. This paper proposes a fast computational tool for feasibility screening of natural gas load profiles. It first establishes the theoretical results on the convexity of loadability regions with sufficient conditions. Then, an asymptotic algorithm is applied to compute a sequence of inner polytopes that converges to the convex loadability region. Each polytope in the sequence can serve as a certificate for feasibility. The conservativeness of this inner estimation will decline along the monotone sequence. The algorithm is testified on a modified realistic Belgian natural gas system with multi-dimensional load profiles.