Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “RESOURCES”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM). Final Report

Distributed Resources for the Earth System Grid Federation (ESGF) Advanced Management (DREAM) is a proposed system that will enable data from an infinite number of diverse sources to be organized and accessed from anywhere using any handheld or other computer device. The approach offers a powerful roadmap for the creation and integration of a unified knowledge base of an entire ecosystem, including its many geophysical, geographical, social, political, agricultural, energy, transportation, and cyber aspects. The resulting aggregation of data has the potential to generate an informational universe of unprecedented size that has never before been possible due to the prohibitive costs, managerial complexity, and technical barriers associated with ever-changing exponential-growth data flows. We envision that DREAM will accelerate discovery by enabling climate researchers, among other types of researchers, to manage, analyze, and visualize data from earth-scale measurements and simulations. DREAM’s success will be built on proven components that leverage existing services and resources. A key building block for DREAM will be the ESGF, chaired by Dean N. Williams. Expanding on the existing ESGF, the project will ensure that the access, storage, movement, and analysis of the large quantities of data that are processed and produced by diverse science projects can be dynamically distributed with proper resource management. Much of the Office of Science data is currently generated by multiple stand-alone facilities. DREAM can collect data accumulated from these facilities and incorporate it into a fully integrated network accessible from anywhere in the world. The result is a completely new paradigm shift for data management, analysis, and visualization enabling researchers to: Manage their calculations, data, tools, and research results; Ensure that all data are sharable, reproducible and (re)usable—accompanied by appropriate metadata describing its provenance, syntax, and semantics at creation; Advance application performance by selectively adapting APIs and services in response to scientific requirements and architectural complexities; and Provide scalable interactive resource management—navigate data and metadata at multiple levels, provide architecture-aware data integration, analysis and visualization tools. We will engage closely with DOE, NASA, and NOAA science groups working at the leading edge of computing. These engagements—in domains such as biology, climate, and hydrology—will allow us to advance disciplinary science goals and inform our development of technologies that can accelerate discovery across DOE more broadly. We will advertise and promote our technologies via dedicated workshops, tutorials, and sessions at conferences, stand-alone events with broad inter-disciplinary invitation, and engagements with leadership facilities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Resource for the Development of Biomedical Accelerator Mass Spectrometry (AMS) Final Report

The NIH Research Resource for Biomedical AMS was originally funded at Lawrence Livermore National Laboratory in 1999 to develop and apply the technology of accelerator mass spectrometry (AMS) in broad- based biomedical research. The Resource’s niche is to fill needs for ultra high sensitivity quantitation when isotope-labeled agents are used. The Research Resource’s Technology Research and Development (TR&D) efforts will focus on the needs of the biomedical research community in the context of seven Driving Biomedical Projects (DBPs) that will drive the Center’s technical capabilities through three core TR&Ds. We will expand our present capabilities by developing a fully integrated HPLC AMS to increase our capabilities for metabolic measurements, we will develop methods to understand cellular processes and we will develop and validate methods for the application of AMS in human studies, which is a growing area of demand by collaborators and service users. In addition, we will continue to support new and ongoing collaborative and service projects that require the capabilities of the Resource. The Center will continue to train researchers in the use of the AMS capabilities being developed, and the results of all efforts will be widely disseminated to advance progress in biomedical research. Towards these goals, our specific aims are to:1.) Increase the value and information content of AMS measurements by combining molecular speciation with quantitation of defined macromolecular isolates. Specifically, develop and validate methods for macromolecule labeling, characterization and quantitation.2.) Develop and validate methods and strategies to enable AMS to become more broadly used in human studies. Specifically, demonstrate robust methods for conducting pharmacokinetic/pharmacodynamics studies in humans and model systems.3.) Increase the accessibility of AMS to the Biomedical research community and the throughput of AMS through direct coupling to separatory instruments.4.) Provide high throughput 14C BioAMS analysis for collaborative and service clients.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

BEE - FY20 P6-2: Support for HPC resource managers 2.3.6.01 – LANL ATDM ST / STNS01-6 P6 Milestone Completion Documentation

BEE uses abstract interfaces between core functionality and specific driver code. An example of this is the worker_interface. The worker_interface is used by the BEETaskManager to communicate with the HPC system-specific resource manager (e.g. Slurm) and container runtime (e.g. Charliecloud). BEE initially only supported the Slurm HPC resource manager. This activity will make HPC resource manager support a configurable option. When this activity is complete BEE will support both the Slurm and LSF resource managers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Workshop on Research Needs for Offshore Wind Resource Characterization: Summary Report

The U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy’s Wind Energy Technologies Office convened “Research Needs for Offshore Wind Resource Characterization,” a workshop in Alexandria, Virginia, on March 5–6, 2019. Wind resource characterization includes meteorological information to estimate annual energy production, forecasts to ensure economical and reliable wind energy integration, and turbulence characterization for developing and applying design load criteria. The purpose of the workshop was to bring together representatives from the offshore wind industry and marine environmental research community to share views on meteorological and oceanographic information needed to successfully develop offshore wind projects in the United States. It was also intended to identify current industry knowledge gaps that can be effectively addressed by researchers with current and emerging observational and modeling tools. The workshop was in response to one of the key challenges articulated in the National Offshore Wind Strategy: reducing costs and technology risks through improved offshore wind power resource and site characterization. The strategy noted that “a better understanding of the unique meteorological, ocean, and seafloor conditions across U.S. offshore wind development sites will allow for optimized designs, reduced capital costs, greater safety, and less uncertainty in preconstruction energy estimates, resulting in reduced financing costs.” The workshop built on the National Offshore Wind Strategy, as well as previous workshops and reports that have informed this research area, providing the basis for future investment in offshore resource characterization research. The 1.5-day workshop involved 55 participants with comparable numbers of representatives from industry, academia, national laboratories, and federal agencies. The meeting included a small number of participants from Europe. The structure was to seed discussions with presentations by national and international leaders in their respective disciplines, followed by discussion among all participants. Discussion began with current industry needs and gaps for metocean information from the European perspective as well as considering unique aspects of the U.S. offshore environment. Those topics were followed by discussion of information needs specifically to address offshore wind system design requirements. These sessions provided the context for the third primary area of discussion, which was current capabilities and challenges for the research community in providing the needed information. This input will inform DOE, other state and federal agencies, research institutions, and industry stakeholders in making decisions about potential research and development (R&D) efforts supporting the development of offshore wind energy in the United States.

17 WIND ENERGY↗
DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness - An Introduction to the Open-Source Tool and Use Cases

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Quantifying the Solar Energy Resource for Puerto Rico

After Hurricane Maria, multiple U.S. Department of Energy laboratories studied the state of the electric grid in Puerto Rico and analyzed grid resilience and grid integration of renewable energy. As part of the work done at the National Renewable Energy Laboratory, researchers created new solar resource data, conducted a technical potential and supply curve analysis, and studied the interannual variability of the solar resource. A new methodology was developed to downscale solar resource data from the National Solar Radiation Data Base (NSRDB) from a 4-km x 4-km spatial and 30-minute temporal resolution to a 2 km x 2 km and 5-minute resolution. This methodology primarily used simple physical principles to develop high-resolution cloud properties which were then used to compute solar radiation. The high-resolution datasets were validated against ground measurements and the error metrics were found to be similar to the original lower resolution dataset. Using 20 years of downscaled data from the NSRDB multi-year capacity factors for photovoltaics (PV) were developed for both single-axis tracking and fixed latitude-tilt configurations. Use of the multi-year data provides the ability to understand variability in capacity factors due to variability in weather over a long period of time. For Puerto Rico the coastal regions were found to have significant higher capacity factors than inland. Using land-use and terrain information a technical potential analysis was conducted for Puerto Rico. This analysis restricted single PV plant development to a maximum of 100 MW nameplate capacity. The nameplate capacity for each municipality were then determined. Based on our assumptions, 56 of the 78 total municipalities of Puerto Rico contain some level of solar capacity. Most of the interior municipalities did not have any capacity because of the geographic exclusions used in this study. The lowest capacity for a PV plant observed in a municipality was 10 MW. The maximum capacity within a county was 2,000 MW. Further a supply curve analysis was conducted by taking the results of the technical potential and quantifying system and transmission costs. The levelized cost of energy (LCOE) was calculated for each theoretical PV plant site, and the levelized cost of transmission was added to the LCOE to produce a total cost estimate for each site. The results of the supply curve analysis allow for a relative comparison of the cost for integrating new PV capacity into the grid. This analysis indicates that cheaper total LCOE sites tend to be larger in capacity. The total capacity in this study was found to be far beyond the maximum peak load for the island. However, this study does not consider the economic and market potential for development. The cumulative capacity presented in this study assumes that the best locations are developed first and ignores the complex decision paths for new power plant development. Therefore, this analysis can only be treated as illustrative. Finally this study investigates the impact of inter-annual variability of resource using a variety of metrices including probability of exceedance and variation in capacity factor and LCOE. This study demonstrates that the capacity factor or LCOE could vary by over 10% year to year. This clearly indicates the risks involved in using any particular year of data and clearly points to the use of multi-year data to reduce some of the risks related to variability in weather.

14 SOLAR ENERGY↗
DOE OSTI2022

Renewable Energy Resource Assessment Information for the United States

The Renewable Energy Resource Assessment Information for the United States report summarizes the results of nearly 30 national renewable energy resource assessments performed by the U.S. national laboratories since 2012. Included are assessments for solar, wind, biomass, marine, geothermal, and hydropower energy resource technologies. Increased attention is given to the renewable energy resources available near federally recognized Tribal Nations and low-to-moderate income households, where assessed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Opportunities for Recovering Resources from Municipal Wastewater

Municipal wastewater contains valuable resources including water, energy, and nutrients that often enter and leave wastewater treatment plants (WWTPs) without being captured. Currently, plants are increasingly seeking to recover resources and reuse them in a sustainable way. Therefore, the purpose of this project was to assess the potential for recovery and reuse of water and products from municipal wastewater treatment plants across the United States and to examine how this potential varies by region. To accomplish this, three main tasks were set: first, to characterize wastewater treatment plants; second, to characterize technologies and pathways used to recover energy, nutrients, and water from treatment plants; third, to assess the demand for reclaimed resources and products at a regional level by performing spatial analysis. These three tasks were then synthesized to present key findings in this report and a geospatial dataset with the hope of guiding the increased use of resource recovery technologies in the U.S.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Battery Energy Storage Scenario Analyses Using the Lithium-Ion Battery Resource Assessment (LIBRA) Model

Meeting aggressive carbon emission goals will entail widespread deployment of renewable sources of electricity. Because these sources are variable, there is a need to develop scalable energy storage technologies. The U.S. Department of Energy is supporting efforts to increase U.S. manufacturing and recycling capabilities for LIBs and to decrease costs of stationary storage batteries. Many factors influence the domestic manufacturing and cost of stationary storage batteries, including availability of critical raw materials (lithium, cobalt, and nickel), competition from various demand sectors (consumer electronics, vehicles, and battery energy storage), resource recovery (recycling), government policies, and learning in the industry, among other factors. Understanding how these factors interact and identifying synergies and bottlenecks is important for developing effective strategies for the LIB stationary energy storage system. We developed the Lithium-Ion Battery Resource Analysis (LIBRA) model as a tool to help stakeholders better understand the following types of questions: What are the roles of R&D, industrial learning, and scaling of demand in lowering the cost of battery energy storage system production? How do the intersections between the EV and stationary storage sectors affect the battery supply chain? For various stationary storage and EV penetration scenarios, what volumes of critical materials might be required and what role can resource recovery play? What does expected demand for both EVs and stationary storage portend for mineral resources and overall mineral scarcity? The LIBRA model is developed using a System dynamics (SD) modeling approach to represent interactions across the segments of the battery materials supply chain. System dynamics models can capture the complex interactions and feedback between the various system components that influence supply and demand. The LIBRA model is comprised of several interacting modules that represent specific portions of the LIB supply chain. The model tracks the buildout of the domestic LIB industry over time (2020 - 2050) and in the context of competing demands for raw materials, recycling, and markets for LIBs. The LIBRA model represents major systemic feedback loops and delays across the supply chain. This report provides a complete documentation for the LIBRA model, including model assumptions, data, scenario analysis results, and sensitivity analysis of the model's input space.

25 ENERGY STORAGE↗
DOE OSTI2022

Price Formation and Grid Operation Impacts from Variable Renewable Energy Resources

Increasing amounts of Variable Renewable Energy Resources (VREs) impact electricity markets and their operation. VREs are intermittent, zero marginal cost resources that tend to displace emissions-intensive generators in electricity dispatch, reducing emissions, but impacting price formation, revenue sufficiency, reliability, and market power mitigation processes of electricity markets. But VREs are not the only factor that affects operational and financial challenges in electricity markets. Declining natural gas prices, changing resource mixes, as well as different electricity market designs and regulatory policies all factor into the challenges both electricity market participants and operators face in today’s electricity markets. With this in-depth examination of electricity markets and related literature review, we aim to inform on key challenges of market design and operation for successful integration of large amounts of zero marginal cost resources. We’ve identified several areas, including VREs impact on price formation, revenue sufficiency, reliability, market power monitoring and mitigation, as well as how state-level incentives and market design impact VREs and these challenges. With each key challenge, we survey the literature to answer the question: To what extent is the problem, and how has it evolved over time? We first conduct a thorough review of ongoing challenges in electricity markets to understand the problem and review the empirical literature to capture important findings on how VREs, specifically, impact the problem. From this review, we highlight metrics that are important to understanding VRE integration and how market designs and outcomes are evolving with increasing levels of VREs. We propose several empirical models for future research to determine the impact of VREs on these identified challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale that has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify highvalue data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies.

58 GEOSCIENCES↗
DOE OSTI2024

Community Energy Storage Financing: Resources and structures under the Inflation Reduction Act

New federal financial resources are available to community-based energy storage projects and new financing structures are emerging in response. Many of these new resources arise from the Inflation Reduction Act of 2022, which makes billions of dollars available for clean energy technology like energy storage. It also makes clean energy tax credits available to certain community entities through a new elective pay mechanism. These new resources are a significant opportunity. Navigating their nuances may be challenging. This paper aims to identify and raise awareness of these developments and serve as a resource guide for community entities considering or pursuing community energy storage. The paper is arranged around key financial considerations that a community entity might weigh: the benefits desired from the project, the costs to provide those benefits, project ownership, pursuing tax credits, and additional sources of capital. These considerations give rise to several potential financial structures that are identified and finally compared.

25 ENERGY STORAGE↗
DOE OSTI2024

​Understanding a Stratigraphic Hydrothermal Resource – Geophysical Imaging at Steptoe Valley, Nevada

Sandia National Laboratories partnered with a multi-disciplinary group of subject matter experts to evaluate a stratigraphic geothermal resource in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The stratigraphic reservoir in northern Steptoe Valley was previously discovered during oil and gas exploration. Subsequent studies, such as the Nevada Play Fairway Analysis, included data which further highlighted potential resource targets in the basin. Geophysical surveys, complemented with refined geologic mapping and geochemical sampling, were deployed to further characterize the resource. The resulting 3D geologic interpretation, conceptual model refinements, and reservoir simulations suggest that a >100MWe power-capable reservoir is likely economically accessible using conventional well placement and stimulation techniques in the Paleozoic carbonates of the deep/central basin of northern Steptoe Valley. Additional geophysical characterization and exploration drilling efforts are recommended to calibrate interpretation and determine where/how to potentially develop the northern Steptoe resource. The geophysical tools, interpretations, lessons learned, and public data generated by this study establish an exploration methodology to inform decisions for characterization and development of northern Steptoe Valley and other stratigraphic geothermal reservoirs in the western U.S.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

NFPA Distributed Energy Resources Safety Training (DERST) For Emergency Responders

The National Fire Protection Association, with support from the Department of Energy, executed a multi-year initiative to develop, enhance, and disseminate Distributed Energy Resources Safety Training (DERST) tools for U.S. emergency responders. As Distributed Energy Resources (DER)—such as solar photovoltaics, battery energy storage systems (ESS), electric vehicles (EVs), and associated infrastructure—become increasingly prevalent, the NFPA identified a critical need for up-to-date standardized, accessible, and effective safety training tailored for the fire service and related public safety professionals. The project delivered a comprehensive suite of educational resources to improve responders’ abilities to safely manage DER-related incidents. This included: • Revised Modular Training Courses: Updated classroom-based DER safety courses, now modular and accessible nationwide through fire academies and the North American Fire Training Directors (NAFTD) network. • Live Burn Testing & Research: A full-scale controlled burn of a DER-equipped residential structure provided real-world data and insights, forming the basis for updated best practices. • A Gamified Simulation Tool – Firefighters Incident Response Simulation Tool (FIRST): A first-of-its-kind, multiplayer, scenario-based simulation using the Unreal Engine 5.0 to train responders in a realistic virtual, multi-DER incident environment. • Field Familiarization Software Tools & Prop Guide: Digital DER field familiarization evolutions software guide and a prop development manual to support field-based DER training exercises, enhancing responders' hands-on familiarity with DER infrastructure and collaboration on virtual incident responses. • National Dissemination Strategy: Strategic partnerships with NAFTD, Vector Solutions, and others enabled wide-scale distribution, with over 5,000 departments accessing resources and 1,100+ departments adopting the simulator in the first seven months. Also provided a web portal for easy access to all training and simulation programs developed under this grant for the U.S. responder community. Key findings from the project—particularly from the burn test—led to paradigm shifts in fire response tactics. For example, traditional approaches to garage fires may be hazardous if DERs are present, due to explosive off gassing and thermal runaway risks. The new training emphasizes scene assessment, stand-off approaches, thermal imaging verification, and careful post-incident cooling of DER components to prevent reignition. This initiative has had a significant national impact, raising awareness, enhancing preparedness, and supporting safer DER incident response practices. Significant engagement from the media, public safety organizations, and PBS coverage has further amplified the reach and adoption of NFPA’s DER safety training, tools, and simulations.

14 SOLAR ENERGY↗
DOE OSTI2023

Resource Adequacy for State Utility Regulators: Current Practices and Emerging Reforms

This report was developed by staff in the National Association of Regulatory Utility Commissioners (NARUC) Center for Partnerships and Innovation (CPI). Additional support was provided from commissioners, commission staff, and other technical experts to provide foundational information for state utility regulators on the evolving nature of resource adequacy for the electric system. With the changing nature of the system, state commissioners will continue to play a vital role in their respective jurisdictions. Their roles in overseeing resource decisions are growing in complexity, with consideration for customer costs, state and federal environmental requirements, extreme weather events, fuel supply limitations, generation retirements, shifting requirements for system operators, and growing levels of intermittent and energy-limited resources (e.g., wind, solar, and battery storage). Reliability concerns continue to be an urgent and immediate priority for utility regulators in most parts of the United States. The information in this report is designed to support state commissioners and their respective staff members as they navigate an evolving resource adequacy landscape to maintain reliability amidst a rapidly changing system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

HPC Resource Allocation Under Energy Constraints

We discuss the new problem faced by High-Performance Computing (HPC) facilities in allocating resources to users of their facilities: while facilities once allocated a single finite resource—node-hours—now facilities must also concurrently allocate a second scarce resource: electrical energy, which is bounded within each facility's annual operations budget. Current application optimization practices encourage conservation of the first resource, but can be potentially unaffordably wasteful of the second. We describe a framework for reasoning about such allocations that can be utilized by facilities to articulate policy, while encouraging scientific application developers to write code mindfully of both constraints. We outline the requirements on facilities, on developers, and on hardware vendors and integrators that are necessary to enable the implementation of this framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Bioinformatic teaching resources - for educators, by educators - using KBase, a free, user-friendly, open source platform

Over the past year, biology educators and staff at the Department of Energy Systems Biology Knowledgebase (KBase) initiated a collaborative effort to develop a curriculum for bioinformatics education. KBase is a free and easily accessible data science platform that integrates many bioinformatics resources into a graphical user interface built upon reproducible analysis notebooks. KBase held conversations with college and high school instructors to understand how KBase could potentially support their educational goals. These conversations morphed into a working group of biological and data science instructors that adapted the KBase platform to their curriculum needs, specifically around concepts in Genomics, Metagenomics, Pangenomics, and Phylogenetics. The KBase Educators Working Group developed modular, adaptable, and customizable instructional units. Each instructional module contains teaching resources, publicly available data, analysis tools, and markdown capability to tailor instructions and learning goals for each class. The online user interface enables students to conduct hands-on data science research and analyses without requiring programming skills or their own computational resources (these are provided by KBase). Alongside these resources, KBase continues to work with instructors, supporting the development of additional curriculum modules. For anyone new to the platform, KBase, and the growing KBase Educators Organization, provides a community network, accompanied by community-sourced guidelines, instructional templates, and peer support to use KBase within a classroom whether virtual or in-person.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Closed Loop Pumped Storage Hydropower Resource Assessment of the United States

The data includes a geospatial and spreadsheet representation of a resource analysis for closed loop pumped storage systems across the Continental United States, Alaska, Hawaii, and Puerto Rico. The data includes energy storage potential, water volume, distance from source to storage, hydraulic head, dollars per kilowatt of storage, and transmission spurline cost for each pumped storage hydropower (PHS) reservoir. Each reservoir represented in this dataset is represented on potential 10 hour storage duration PSH system comprised of two reservoirs. Units of measure are laid out in the dataset. Pumped storage hydropower (PSH) represents the bulk of the United States' current energy storage capacity: 23 gigawatts (GW) of the 24 GW national total (Denholm et al. 2021). This capacity was largely built between 1960 and 1990. PSH is a mature and proven method of energy storage with competitive round-trip efficiency and long life spans. These qualities make PSH a very attractive potential solution to energy storage needs, particularly for longer-duration storage (8 hours or more); such storage will be crucial to bridge gaps in electricity production as variable wind and solar production continue to comprise an ever-larger portion of the United States' energy portfolio. This study seeks to better understand the technical potential for PSH development in the United States by developing a national-scale resource assessment for closed-loop PSH. For more information, please refer to the Closed Loop Pumped Storage Hydropower Resource Assessment for the United States linked in the resources.

Array↗