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An Energy-Water Nexus Foundation Model Ecosystem to Advance System Resiliency and Affordability

This white paper presents how an AI-driven foundation model ecosystem for hydropower and the electric grid, integrated with a large language model (LLM) agent can address the "Water for Energy" challenge and modernize coordinated planning and operations of the U.S. energy-water ne...

Kwon, J., Kim, K., Levin, T., and Botterud, A.

AI-Enhanced Hydropower Systems: Smart Dams for a Resilient Future

This paper focuses on water-energy, using AI for smart, holistic hydropower operations to enhance water for energy resilience. The existing challenges include (a) increasing demand for water and electricity, requiring a shift to flexible, real-time hydropower operations due to ch...

Varadharajan, C., Ajami, N., Brodie, E., Ciulla, F., Falco, N., Feldman, D., Newcomer, M., Dwivedi, D., Li, Y., Nakata, R., Nakata, N., Nico, P., Williams, K., Mahoney, M., Ramakrishnan, L., and Cholia, S.

Maximizing American Energy Dominance with Forecasts of Energy Infrastructure Flood Exposure and AI Predictions of Consequences

This white paper focuses on water for energy. High frequency, reliable, and spatially explicit flood forecasts are necessary to forecast impacts to the energy system from hydrological hazards. While these tools are nearing operation at scale, they have not yet been systematicall...

Brelsford, C., Garcia, M., Robbins, Z., Schwenk, J., and Liu, Y.