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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.

Supporting adoption of advanced forecast informed reservoir operations tools to improve agricultural and municipal water and energy outcomes

Expanding the use of advanced forecast-informed reservoir operations tools can optimize or improve water delivery and storage for energy generation, irrigation, and municipal uses. Advanced forecast-informed data and tools are increasingly being integrated into large-scale reservo...

Jorgensen, J., Giovando, J., Pracheil, B., Hou, H., and Niazi, H.

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.

Revolutionizing Water-Energy Infrastructure Resilience through Distributed Sensing and Digital Twins

This white paper addresses the intersection of Water for Energy and Energy for Water, proposing foundational technology to enhance the resilience and operational longevity of critical national assets, including hydropower facilities and marine energy systems. The core challenge i...

Luo, L.

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.

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.

Unlocking Hydropower Potential from Environmental Flows for Energy-Water Resilience

This white paper examines how mandated environmental flow (E-flow) releases at hydropower dams can be leveraged to generate renewable energy while maintaining ecological integrity. Environmental flows sustain aquatic ecosystems but often bypass turbines, representing lost generati...

DeNeale, S., Connor, M., and McManamay, R.

Forecast and Intelligence Enabled Reservoir Operations for Energy-Water Resilience

This white paper discusses the energy-water nexus and emphasizes the need for co-optimization of hydropower, reservoir management, and water supply operations to enhance resilience and reliability. It focuses on integrating water management intelligence with power system forecasti...

Sun, M., and Hansen, C.

Forecast-Informed, Market-Responsive Conjunctive Operations for Multi-Reservoir Water-Energy Systems

The white paper, "Forecast-Informed, Market-Responsive Conjunctive Operations for Multi-Reservoir Water-Energy Systems" , addresses the water-for-energy and energy-for-water nexus by proposing a framework for co-optimizing hydropower and cascading reservoir operations alongside fl...

Pavicevic, M., Mork, E., Yu, A., Herman, J., Emmons, J., and Ploussard, Q.

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.

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