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Reinforcement Learning for Water-Energy Infrastructure Resilience and Evolution

This white paper outlines a foundational AI-based framework for improving resilience across the energy-water nexus, with a focus on electric grid and water system interdependencies under hydrologic and weather extremes. The focal area spans both "water for energy" and "energy for ...

Jackson, N., and Rao, N.

Integrated Water-Energy Resilience Research and Testbeds

Water availability increasingly constrains the reliability and flexibility of water-dependent energy systems, including hydropower, thermoelectric generation, and grid operations. Hydrologic extremes, shifting demand, aging infrastructure, and cross-sector pressures are intensifyi...

Negron-Juarez, R., Amusat, O., Koven, C., and Viers, J.

Gaps Between Western U.S. Reservoir Inflows and Headwater Precipitation Timing, Amount, and Phase

Snowmelt from mountain headwater basins supplies approximately 80% of the runoff to reservoirs in the western United States (WUS), and is therefore a key component of western hydropower. Yet predicting runoff from hydrometeorological data in complex terrain (and its sensitivity to...

Rudisill, W., and Feldman, D.

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.