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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.

Hydrotwin: an AI-based physics and optimization framework for improved water resource resilience in systems experiencing adverse events

This white paper focuses on water for energy. As we move ahead into an uncertain future for water resource demand and supply, a massive challenge exists to optimize water systems to be resilient to a range of press/pulse extreme event states and conditions. Optimal decision-makin...

Bennett, K., Schwenk, J., and Garcia, M.

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.

Energy-Efficient Water Management Using Geo-AI for Evapotranspiration and Crop Risk Analysis

This white paper outlines a strategy for enhancing energy-efficient water management in agriculture through the application of Geospatial Artificial Intelligence (GeoAI). The focus is on developing a Dynamic Irrigation Window Scheduling (DIWS) system that optimizes irrigation base...

Cafferty, K., and Pacheco, C.