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Energy-Water Resilience

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Showing results 31 - 39 of 39.
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Thermoelectric and Hydropower Drought Monitor and Outlook: Tools for more robust resource adequacy planning and management

The primary focus is on issues related to water for energy; specifically, how drought-impacted water supply limits the generation potential of hydropower and thermoelectric assets. Existing Challenge: Twenty-two droughts, each causing a billion dollars or more in damages have im...
Voisin, N., Tidwell, V., and Gerlich, J.

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.

Quantifying Energy Use across U.S. Water Sectors: A Scalable AI/ML-Driven Framework for Data Integration and Resilience Planning

This white paper explores opportunities to quantify and characterize energy use across major U.S. water sectors, including irrigation, water supply, and water treatment, with a focus on energy for water dimension. A scalable AI/ML-driven framework will be developed to harmonize fr...
Ghimire, G., Bhanja, S., and Martinez, R.

Maximizing American Energy Dominance with Forecasts of Energy Infrastructure Flood Exposure and AI Predictions of Consequences

This white paper focuses on water for energy. High frequency, reliable, and spatially explicit flood forecasts are necessary to forecast impacts to the energy system from hydrological hazards. While these tools are nearing operation at scale, they have not yet been systematicall...
Brelsford, C., Garcia, M., Robbins, Z., Schwenk, J., and Liu, Y.

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.

A Framework for Improving Locational Marginal Price Estimates for Technoeconomic Analysis of Hydropower Investments and Operational Decisions

The focus is on improving the analytics supporting hydropower investment decisions through the more accurate characterization of the locational marginal prices (LMPs) that will define future energy payments. Enhanced analytics around LMP prediction could also be used to improve op...
Balducci, P., DeSomber, K., and Zhou, Z.

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.

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.

From Modeling to Testbeds: Taking an Expanded Look at Wastewater Reuse

The primary focus is on energy for water, considering the myriad tradeoffs influencing the adoption of wastewater reuse, particularly considering its energy intensity. Wastewater reuse offers a compelling opportunity to concurrently tackle water scarcity and enhance energy effic...
Tidwell, V., Bixler, T., Niazi, H., Marsh, P., and Wild, T.

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