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Employing AI-Enabled Prognostics for Energy-Water Resilience

This white paper focuses on strengthening the resilience and efficiency of hydropower systems at the energy-water nexus through AI-enabled prognostics and hardware-in-the-loop (HIL) simulation. It emphasizes integrating digital intelligence with physical infrastructure to optimize...

Zhao, S., Qiu, F., and Agalgaonkar, Y.

Enabling Energy-Water Resilience in U.S. Data Centers: Water-Aware Grid Planning and Operations with Infrastructure-Compatible Cooling

Rapid, concentrated expansion of AI data centers is reshaping electricity demand profiles, local infrastructure requirements, and regional resource constraints. These facilities are often sized from tens to hundreds of megawatts with multi-gigawatt campus clusters. They are relati...

Zhou, Z., Wu, M., Qiu, F., Muehleisen, R., Zhao, D., Yan, E., and Worek, W.

Integrated Planning for Resilient Energy-, Infrastructure-, and Hydro-Scapes

The focus of this paper is nationally-comprehensive, hyper-granular assessment of future energy expansion opportunities and challenges, considering multi-dimensional risks and consequent implications of large infrastructure additions on surface water and groundwater, spanning from...

McCollum, D., Rathore, S., Liu, Y., and Parish, E.

Water Energy Planning Strategies to meet Emerging Load from Data Centers

This white paper discusses the urgent need for innovative management of energy and water resources in the context of rapidly growing data centers, particularly as U.S. electricity demand is projected to increase by 35 to 40% by 2040 due to the rise of artificial intelligence (AI)....

Bhowmik, P., Cafferty, K., Klise, K., and Jackson, N.

Agentic Optimization for Resilience in Hydropower Reservoir Systems

The growing electricity demand in the U.S. requires a resilient energy strategy. Hydropower is a major component of that strategy but is subject to environmental and human stressors that impact its dependability. AI-driven reinforcement learning, called "Agentic" learning, presen...

Schwenk, J., Garcia-Cardona, C., Bennett, K., Singh, S., and Brelsford, C.