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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The Third Assessment of the Effects of Climate Change on Federal Hydropower

Understanding the future changes in projected water supplies is a vital objective for federal hydropower facilities tasked with providing low-cost, reliable electricity across a large regional footprint that encompasses a growing customer base, alternative market structures for marketing the electricity, and a more diverse generation asset mix than was historically present when a majority of federal hydropower facilities were built. This study, The Third Assessment of the Effects of Climate Change on Federal Hydropower, directed by Section 9505 of the SECURE Water Act of 2009 (SWA), is the third quinquennial report on evaluating the effects of climate change on hydroelectric energy generated from 132 US federal hydropower plants marketed by four US Department of Energy (DOE) Power Marketing Administrations (PMAs). The technical assessment is conducted by DOE’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Texas A&M University under the guidance of DOE’s Water Power Technologies Office. This study is the result of extensive consultation with the four federal PMAs (Bonneville Power Administration [BPA], Western Area Power Administration [WAPA], Southwestern Power Administration [SWPA], and Southeastern Power Administration [SEPA]), as well as other agencies, including federal hydropower owners/operators (the US Army Corps of Engineers, US Bureau of Reclamation [Reclamation]), US Geological Survey, and National Oceanic and Atmospheric Administration). The main findings of this assessment, along with the PMA administrators’ recommendations, will be included in a subsequent DOE report to Congress. The assessment method and the technical findings are described in this report.

13 HYDRO ENERGY↗
DOE OSTI2025

Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower (DIVERS-H)

U.S. hydropower plants face potential threats from shrinking water supply, rising demands, and warmer stream temperatures from various causes. Power plant owners, operators, and regulators require new tools to take advantage of and interpret the diverse range of scientific data being produced by both observational methods (for example, satellite, radar, stream gauges) and computer modeling methods that evaluate and predict how earth's dynamic systems (atmosphere, oceans, land surface, and sea ice) are changing and interacting. Combining datasets such as these with AI-based analyses introduces a novel decision support system to help users anticipate and address potential impacts on power generation stations. This new technology has been named DIVERS-H for "Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower." In Phase I, technical feasibility was established with the development and demonstration of all the new technologies that are required. Most notably, DIVERS-H will use new artificial intelligence (AI) methods to capture the complex dynamics of water availability, demand, and environmental changes. In addition, new data management software was developed, and a prototype user interface was implemented as the precursor to a full scale decision support system. With technical research complete, the project focus now shifts to development of a commercial software product to provide users with actionable insight into water availability and the risk/resilience of critical systems at their locations of interest. Although DIVER-H was originally conceived as a tool for hydroelectric power applications, the same underlying technology can be readily applied to other water-consuming systems including coal, natural gas, oil, and nuclear power plants.

Chaudhary, Aashish [Kitware, Inc., Clifton Park, N↗
DOE OSTI2026

Alaska Observed Hydropower Generation

This dataset contains compiled observed hydropower generation for hydropower plants in Alaska. Data have been compiled from data provided to the Energy Information Administration by asset owners, data contained in annual reports produced by the Institute of Social and Economic Research at the University of Alaska Anchorage (Alaska Electric Power Statistics and Alaska Energy Statistics) and data provided to the Federal Energy Regulatory Commission by asset owners. This dataset provides available generation data from all sources in monthly and annual files, with quality flags, and generation data identifying the highest quality source in monthly and annual files.

hydropower datasets↗
DOE OSTI2024

Paired Hydro-Battery Hybrid System Operations Using MIQP Based Multi-Objective Optimization

Hybridizing a hydropower plant with a battery energy storage system is often a very expensive decision. So to make the case for feasibility of hybridization the cost benefit analysis must be comprehensive. Most literature found on this subject only uses one out of many different available value streams to carry out a feasibility analysis. To that end, in this study we propose a multi-objective optimization formulation and a mixed-integer quadratic programming optimization engine that considers multiple different value streams and optimizes hydro-battery hybrid system paired operations to maximize revenue generated from energy arbitrage while simultaneously minimizing the total hydro turbine mileage thus reducing turbine starts and stops and improving turbines life all while following all environmental constraints and not violating any limitations either regulatory or preferential (i.e., to support recreational activities like white water rafting, etc.). In this study we also implemented the developed optimization methodology to a real-world case study of Bagnell dam hydropower facility (8 units totaling 240 MW rated power capacity) which is owned and operated by our industry partner Ameren Energy Inc. The case study outcomes shows that by hybridizing the Bagnell dam hydropower facility with a 60 MW x 2-hr battery energy storage system, the annual benefits can be increased over \$6 million while reducing the annual mileage averaged per turbine and number of start/stops by over 98\% and 85\% respectively.

Chalishazar, Vishvas H.↗
DOE OSTI2025

Financial Analysis of the High Flow Experiment conducted at the Glen Canyon Dam during Water Year 2023

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specified criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report examines the financial implications of the high flow experiment (HFE) conducted at GCD during the spring of Water Year (WY) 2023 as required by the LTEMP HFE Protocol. This report is part of a series of reports that describe the financial costs of LTEMP experimental releases since the 2016 ROD was adopted in January 2017. Previous reports analyzed the impact of several past HFEs and Bug Flow Experiments. This report focuses on the HFE conducted in April 2023. For this experimental release, financial costs of approximately $1.33 million were incurred because the HFE required sustained water releases exceeding the power plant’s maximum turbine flow rate. In addition, during the experiment, operators were not allowed to shape GCD power production, either to follow Firm Electric Service (FES) customer day-ahead energy deliveries or to respond to market prices. This study identifies the main factors contributing to the HFE costs and examines the interdependencies among these factors. It applies an integrated set of tools to estimate Western Area Power Administration (WAPA) financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the operations that actually occurred and (2) a “Without Experiment” case that simulates operations under the assumption that the HFE did not occur. The “With Experiment” case mimics operations during the HFE and the entire month the HFE occurred. It complies with LTEMP hourly and daily operating criteria. The “Without Experiment” case assumes that the HFE did not occur. The monthly water release volume is assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices. In addition to estimating the financial impact of the HFE, the team used the CRiSPPy model to gain insights into the interplay among ROD operating criteria, exceptions made to criteria to accommodate the HFE, and WAPA operating practices.

13 HYDRO ENERGY↗
DOE OSTI2025

Forty-year hydropower generation reanalysis for Conterminous United States

First published in 2022, the RectifHyd dataset provides hydrologically consistent estimates of monthly net generation for approximately 1,500 hydropower plants in the United States, addressing a gap in industrial surveys that have collected monthly generation data from only ~10% of plants post-2003. Here we present RectifHydPlus—an extended and enhanced dataset that improves on both the proxy information and temporal downscaling methodology adopted in RectifHyd. In addition to providing updated estimates of historical monthly generation for 590 plants with >10 MW nameplate capacity from 1980 through 2019, RectifHydPlus adds a hydrological control dataset that isolates the influence of historical water availability on generation. The new hydrological control dataset is suited to applications seeking to represent the capabilities of the contemporary fleet subject to historical interannual variability in climate. RectifHydPlus also includes a forty-year, daily-resolution, spill-adjusted water release time series for each dam, allowing users to aggregate generation estimates to the desired temporal resolution.

Hydroelectricity↗
DOE OSTI2024

RectifHydPlus Data Pipeline

The RectifHydPlus Data Pipeline is an open source and fully reproducible data processing pipeline for creating RectifHydPlus—a dataset of historical monthly net electricity generation for all US hydropower plants (>10MW). The pipeline is coded in R, applying tidyverse libraries and code principles, and using the targets data pipeline framework. All data inputs to the RectifHydPlus Data Pipeline are available from public sources. References to all data inputs, as well as instructions for running the RectifHydPlus Data Pipeline, are available on the GitLab code repository: https://code.ornl.gov/turnersw/rectifhydplus

Turner, SeanWilliam Donald [Oak Ridge National Lab↗
DOE OSTI2025

RectifHydPlus Data Pipeline v1.1.0

The RectifHydPlus Data Pipeline is an open source and fully reproducible data processing pipeline for creating RectifHydPlus—a dataset of historical monthly net electricity generation for all US hydropower plants (>10MW). The pipeline is coded in R, applying tidyverse libraries and code principles, and using the targets data pipeline framework. All data inputs to the RectifHydPlus Data Pipeline are available from public sources. References to all data inputs, as well as instructions for running the RectifHydPlus Data Pipeline, are available on the GitLab code repository: https://code.ornl.gov/turnersw/rectifhydplus

Turner, SeanWilliam Donald [Oak Ridge National Lab↗
DOE OSTI2025

Financial Analysis of the Smallmouth Bass Flows implemented at the Glen Canyon Dam during Water Year 2024

The Glen Canyon Dam (GCD) is a Colorado River Storage Project (CRSP) power resource that is a component of the Salt Lake City Area Integrated Projects (SLCA/IP). The 2016 record of decision (ROD) for the GCD long-term experimental and management plan (LTEMP) final Environmental Impact Statement (EIS) specifies criteria for GCD monthly water releases, daily and hourly operating limits, and experimental releases. This report presents a financial analysis of the Smallmouth bass (Micropterus dolomieu) (SMB) flows implemented at GCD during Water Year (WY) 2024. These bypass flows were introduced by the U.S. Bureau of Reclamation (USBR) as an emergency response to the growing threat posed by invasive SMB in the Colorado River ecosystem downstream of the dam. SMB are a non-native predatory species that pose a significant threat to native fish populations, including the endangered humpback chub (Gila cypha). The thermal regime below GCD, typically cold due to hypolimnetic releases from Lake Powell, has historically served as a thermal barrier limiting SMB establishment. However, persistently low reservoir levels in recent years have reduced stratification in Lake Powell, allowing warmer water to be released downstream. This has enabled SMB to spawn successfully below the dam, prompting urgent ecological concerns. To mitigate the risk of SMB proliferation, the USBR implemented a series of bypass flows in WY 2024. Drawn from a lower elevation than the penstocks, the bypass structures released cooler water downstream. These short-duration bypass flows aimed to keep temperatures cool enough to prevent SMB from spawning, thereby reducing the ecological threat posed by this invasive species. Although motivated by ecological objectives, these bypass flows came with financial tradeoffs. Releasing water through the bypass structures instead of the turbines at GCD reduced hydropower generation, resulting in a significantly lower financial position for Western Area Power Administration (WAPA), which is responsible for marketing the electricity produced by the GCD Powerplant. This report analyzes the financial impact of the SMB flows implemented from July to November 2024. These experimental releases led to an estimated financial cost of approximately $18.9 million, primarily driven by the substantial volume of water diverted through the bypass structures. This study applies an integrated set of tools to estimate WAPA financial impacts by simulating GCD under two types of cases; namely, (1) a “With Experiment” case that mimics the water operations that actually occurred, including the SMB bypass flows, and (2) a “Without Experiment” case that simulates operations under the assumption that the SMB flows did not occur. Both cases comply with LTEMP hourly and daily operating criteria, and the monthly water release volumes are assumed to be identical under both cases. The Colorado River Storage Project Python-based model (CRiSPPy) model was the main modeling tool used to simulate the dispatch of the GCD hydropower plant and associated water releases from Lake Powell. In the modeling process, the research team used extensive data sets and historical information on SLCA/IP power plant characteristics, hydrologic conditions, and WAPA’s power purchases and sales prices.

13 HYDRO ENERGY↗
DOE OSTI2026

U.S. Hydropower Development Pipeline Data, 2026

The U.S. Hydropower Development Pipeline dataset provides a comprehensive, regularly updated view of proposed and potential hydropower projects across the United States. This resource compiles information from federal agencies and other public sources to track non-powered dams considered for electrification, proposed hydropower facilities at stream reaches with no existing dams, conduit exemptions, and emerging pumped storage hydropower proposals. The dataset includes project characteristics such as location, development status, technology type, ownership category, and other attributes that support analysis of future hydropower trends. It is designed to help researchers, planners, policymakers, and stakeholders assess national‑scale development patterns, understand the evolving hydropower landscape, and explore opportunities and challenges associated with new hydropower deployment. The dataset is updated annually to reflect changes in project status, new proposals entering the pipeline, and projects that are cancelled, completed, or otherwise removed from active consideration. Note: Capacity additions to existing hydropower plants are not included in this database due to reliance on a proprietary data source.

Johnson, Megan [ORNL] (ORCID:0000000290141741)↗
DOE OSTI2024

The 2024 National Hydropower Map

A visualization of the geospatial distribution and characteristics of operational hydropower plants in the United States in 2024.

13 HYDRO ENERGY↗
DOE OSTI2026

The 2026 National Hydropower Map

A visualization of the geospatial distribution and characteristics of operational hydropower plants in the United States in 2026

Schmidt, Erik [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2026

Puerto Rico Observed Hydropower Generation

This dataset contains compiled observed hydropower generation for hydropower plants in Puerto Rico. Data have been compiled from data provided to the Energy Information Administration by asset owners. This dataset provides available generation data in monthly and annual files, with quality flags.

Broman, Daniel P [Pacific Northwest National Labor↗
DOE OSTI2026

Hawaii Observed Hydropower Generation

This dataset contains compiled observed hydropower generation for hydropower plants in Hawaii. Data have been compiled from data provided to the Energy Information Administration by asset owners. This dataset provides available generation data in monthly and annual files, with quality flags.

Broman, Daniel P [Pacific Northwest National Labor↗
DOE OSTI2026

Alaska Observed Hydropower Generation

This dataset contains compiled observed hydropower generation for hydropower plants in Alaska. Data have been compiled from data provided to the Energy Information Administration by asset owners, data contained in annual reports produced by the Institute of Social and Economic Research at the University of Alaska Anchorage (Alaska Electric Power Statistics and Alaska Energy Statistics) and data provided to the Federal Energy Regulatory Commission by asset owners. This dataset provides available generation data from all sources in monthly and annual files, with quality flags, and generation data identifying the highest quality source in monthly and annual files.

Broman, Daniel [Pacific Northwest National Laborat↗
DOE OSTI2022

1.3.3.402 - Cybersecurity Value-at-Risk Framework

The Cybersecurity Value-at-Risk Framework tool will guide users through an assessment and detailed analysis of a hydropower plant's operations. The tool will then provide results and data to inform effective cybersecurity investment decision-making and planning. The results will help managers understand the risk probability of cyberattacks on their facilities and how best to use resources to mitigate those risks.

cybersecurity↗