Seth Blumsack

Compound, consecutive, and cascading hazards increasingly challenge the systemic resilience of critical infrastructure. Among these, the power grid—vital to nearly every facet of society—is uniquely exposed to interdependent stressors from space weather, terrestrial weather, and wildfire. Traditional single-hazard frameworks are insufficient to capture the dynamic, non-linear interactions across these domains thereby being incapable of understanding systemic dynamics and shaping resilience. Drawing on enriched historical event records, statistical network analysis, and sustained engagement with grid operators, we present a new framework for assessing how multi-hazard interactions influence grid resilience. We share event-based storylines—physically self-consistent reconstructions of past events and plausible future pathways—and emergent patterns that reveal both known and previously unrecognized mechanisms of compounding and cascading failure, recovery, and adaptive response. Through investigation of a previously unexamined multi-hazard system (space weather, terrestrial weather, and wildfire) we uncover novel complex behaviors that reframe how resilience and system flourishing can be understood and designed for.Our findings advance methodologies for multi-hazard resilience assessment by integrating physical hazard processes with socio-technical dynamics, including network structure, operator decision-making, and institutional constraints under deep uncertainty. We further outline an emerging global initiative aimed at collective, transdisciplinary action to collect efforts and groups advancing resilience analyses for these ‘wicked problems’ and to collectively explore translating them into adaptive strategies and governance frameworks. By translating multi-hazard insights into actionable knowledge, we offer both methodological tools and institutional pathways for advancing resilience analysis under conditions of deep uncertainty and systemic interdependence.

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.

The power system is undergoing an extensive Energy Transition as the industry faces the combined goals of achieving net-zero carbon emissions while also absorbing increased demand as other energy sectors electrify. Electric power is not only becoming more distributed in nature with increased adoption of customer-sited photovoltaics, energy storage and microgrids, but also has the potential to become highly mobile with the electrification of transportation. Electrification is also increasingly becoming coupled with other energy carriers and systems, including district heating and cooling and thermal energy storage. Effective integration of distributed resources (behind the meter supply and storage), weather dependent renewables, and mobile electric energy supply and storage through electrified transportation requires evolution in planning, operational and control strategies, as well as an appreciation of how people will adopt and use distributed and mobile resources. This mini-track features papers that address advances in modeling, simulation and hardware developments system analyses; and studies of individual and organizational behavior and decision making as pertaining to distributed, renewable and mobile resources in electric power systems. This year's minitrack features two groups of papers. The first session focuses on customer behavior and distribution system performance. These papers address modeling and understanding electricity consumers, demand-side resources and how they interact with the power grid and with one another in increasingly sophisticated ways. The second group of papers in this mini-track addresses the integration of grid-edge technologies into the power grid. Together, the papers in these two sessions address issues connected integrating new customer programs, and grid-edge technologies into the low voltage distribution system.

In operations research and optimization, stochastic programming plays a pivotal role in decision-making under uncertainty. However, solving complex stochastic programs, especially with many scenarios, is computationally challenging. This paper introduces a novel graph-based scenario reduction approach, using bipartite graph theory and community detection algorithms to create a smaller, representative set of scenarios. Unlike many traditional methods, this approach determines the optimal number of scenarios endogenously, improving computational efficiency and robustness. We applied this graph-based method to a two-stage stochastic programming model for power generation expansion planning (GEP), initially comprising 2000 scenarios. Our approach successfully reduced the scenario set while maintaining solution quality. We compare our method with four other techniques—K-means clustering, the Approximate Latent Factor Algorithm (ALFA), Backward Reduction, and Forward Selection. On the GEP problem, the graph-based method yields improved robustness as compared to other methods.

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.

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Generation, microgrids and strategic storage can provide reliability and security and distributed sensing can offer unprecedented system visibility. Integration of DERs requires continuing innovation in coordinated control, optimization, and modeling, and technology to enable the participation in regulation and balancing services, ancillary service markets and distribution system management. How these customer-suppliers will interact with DERs and the larger power grid is still evolving rapidly. Researchers and the industry are starting to realize the potential of data analytics, as well as the potential for distributed and transactive decision-making. There is also increased recognition of the potential for DERs to improve energy-system resilience in the face of extreme events.