OpenEI: Energy Information
  • Energy-Water Resilience
  • My User
    • Sign Up
    • Login
EWR logo
  • White Papers
    • White Papers
  • Help
    • Frequently Asked Questions
    • Contact EWR Help
  • Search
EWR hero logo
Energy-Water Resilience

Search the Library

Showing results 1 - 10 of 56.
Show results per page.
Filters
Submitting Organization
Keywords
"AI/ML-driven framework"×

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.

Reinforcement Learning for Water-Energy Infrastructure Resilience and Evolution

This white paper outlines a foundational AI-based framework for improving resilience across the energy-water nexus, with a focus on electric grid and water system interdependencies under hydrologic and weather extremes. The focal area spans both "water for energy" and "energy for ...
Jackson, N., and Rao, N.

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.

High-Altitude Electromagnetic Pulse (HEMP) effects on Energy-Water resilience

Executive Order 13865 emphasizes the need to focus on critical infrastructure resilience to high-altitude electromagnetic pulse (HEMP) effects, indicating that simulation of EMP effects on both energy and water systems need to be studied. The key technical challenges in assessing ...
Tabarez, J., Barnes, A., and Nelson, E.

Circular Water-Energy Nexus for Resilient Hydrogen Production via Intelligent Seawater Electrolysis and Real-Time Sensing

This white paper addresses the DOE WPTO focal area of energy-water resilience and circular systems, aligned with the topic of water for energy and energy for water cross-optimization. It proposes a machine-learning-enabled circular water-energy platform that integrates hydrogen pr...
Chen, J., and Xiong, G.

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.

A Multi-Scale Integrated Assessment Model for How Emerging Biotechnologies Can Contribute to Decoupling Energy and Water Systems

Energy-water (EW) systems in the U.S. are deeply interconnected through complex networks vulnerable to disruptions, such as when a regional drought simultaneously impacts hydropower generation, thermoelectric production, and water availability across multiple sectors, producing kn...
Patelli, P., Solander, K., Gonzalez-Esquer, R., Xu, C., Bower, C., Davis, R., Carruthers, J., and Thomas, J.

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.

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.

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.

12345Next >>
  • Disclaimers
  • Content is available under Creative Commons Attribution 4.0 unless otherwise noted.

Privacy Policy Notification

This site uses cookies to store and share user preferences with other OpenEI sites, and uses Google Analytics to collect anonymous user information such as which pages are visited, for how often, and what searches or other webpages may have led users here. You can prevent Google Analytics from recognizing you on return visits to this site by disabling cookies on your browser or by installing a Google Analytics Opt-out Browser Add-on. By clicking "Accept" you agree this site can store cookies on your device and disclose information to OpenEI and Google Analytics in accordance with our privacy policy.

OpenEI Privacy Policy Google Analytics Terms of Service