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Advancing Energy-Water Resilience in California: A Framework for Integrated Water and Power Management Opportunities
This white paper identifies opportunities to advance energy-water resilience in California, using the Central Valley Project (CVP) and State Water Project (SWP) system. It addresses the critical intersection of both water for energy and energy for water management, emphasizing how...
Mork, E.
Unlocking Small-scale Hydropower using Water Infrastructure for National Energy Security
Reliable local energy generation and long-duration energy storage are critical to balancing peak demands and providing distributed emergency backup near both urban and rural populations. However, small-scale (< 10 MW) hydropower faces barriers, including siting, permitting, water ...
Stokes-Draut, J., Taylor, M., and Rao, P.
Hybrid Bioenergy and Hydropower Systems: Leveraging Heterogeneous Biomass and Wastes from Watersheds
Sandia National Laboratories and Idaho National Laboratory (INL) explore the water-for-energy nexus in this white paper, focusing on the impact of heterogeneous watershed waste materials on hydropower facilities. They identify key challenges--such as pile burning, wildfires, and d...
Quiroz-Arita, C., and Paudel, 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.
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.
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.
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.
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.
Training, Testing, and Demonstration Capability for In-Conduit Hydropower in Water Systems
This white paper discusses the development of in-conduit hydro turbine testing and training capabilities to enhance energy-water resilience by promoting in-conduit hydropower systems. These systems are installed in irrigation or municipal water distribution pipes, and the project ...
Reese, S., and DeNeale, S.
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.