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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 217 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Impacts of Spatial Resolution in a High-Fidelity Capacity Expansion Model: An ERCOT Case Study

Capacity expansion models are important tools in examining the evolution of the electric power sector. Embedded in these tools are many modeling choices with consequential impacts on computational burden and associated analysis. In this study, we adjust the spatial resolution of the Regional Energy Deployment System (ReEDS) to understand the implications of higher-fidelity modeling on energy system projections and model solve times. The native ReEDS regions capture the contiguous United States in 134 balancing areas whereas the regions in the higher-resolution version are defined by over 3,000 U.S. counties. Using both resolutions, we conduct a case study of the Texas Interconnection (The Electric Reliability Council of Texas [ERCOT]) to explore differences in model projections and to inform appropriate applications of high spatial resolution in a large-scale, applied capacity expansion model.

county↗

DOE OSTI2022

Eulerian simulations of electrostatic waves in plasmas with a single sign of charge

An Eulerian, numerical simulation is used to model the launching of plasma waves in a non-neutral plasma that is confined in a Penning–Malmberg trap. The waves are launched by applying an oscillating potential to an electrically isolated sector at one end of the conducting cylinder that bounds the confinement region and are received by another electrically isolated sector at the other end of the cylinder. The launching of both Trivelpiece–Gould waves and electron acoustic waves is investigated. Adopting a stratagem, the simulation captures essential features of the finite length plasma, while retaining the numerical advantages of a simulation employing periodic spatial boundary conditions. As a benchmark test of the simulation, the results for launched Trivelpiece–Gould waves of small amplitude are successfully compared to a linearized analytic solution for these fluctuations.

Physics↗

DOE OSTI2020

BEPAM-E Model Code and CABBI Simulation Results for "Repeal of the Clean Power Plan: Social Cost and Distributional Implications"

The dataset consists of results and various input data that are used in the GAMS model for the publication "Repeal of the Clean Power Plan: Social Cost and Distributional Implications". All the data are either excel files or in the .inc format which can be read within GAMS or Notepad. Main data sources include: agriculture, transportation and electricity data. Model details can be found in the paper and the GAMS model package.

carbon abatement↗

DOE OSTI2023

Energy-water interdependencies across the three major United States electric grids: A multi-sectoral analysis

As water availability and timing of delivery fluctuates and the US electric grid sees rapid transformation and reconfiguration under decarbonization and resource adequacy strategies, there is a critical need for information and data that supports understanding the water-energy interdependency landscape. The United States currently lacks comprehensive data, informative visualizations, and analysis of energy-water interdependencies at scales necessary to support resource and operational decision-making. This article provides US electricity interconnection-level Sankey diagrams that show the relative reliance of water and energy across various economic sectors. A deeper analysis is additionally provided at the county level to illustrate trends and potential opportunities related to resiliency and efficiency in multi-sectoral water and energy flow distributions and intensities. We find that the electricity interconnections in the US vary dramatically in their water and energy interdependencies across applications and economic sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Building Energy Systems as Behind-the-Meter Resources for Grid Services: Intelligent load control and transactive control and coordination

To mitigate the impacts of climate change, significant reductions in emissions from all sectors of the economy are needed. The electricity generation sector has embarked on an ambitious plan to include renewable generation as part of its decarbonization efforts, and many cities and states are mandating all-electric buildings. While renewable resources will reduce emissions, they are not dispatchable, they vary temporally, and their generation is uncertain. Under these conditions, traditional approaches to managing grid reliability, where supply follows demand, will not be efficient and may not be cost-effective. Further, there is a more efficient alternative for balancing the supply–demand imbalance and for absorbing variability and uncertainty of renewable energy using distributed energy resources (DERs) as opposed to reserve generation. Because buildings consume more than 75% of total U.S. annual electricity consumption, behind-the-meter (BTM) DERs have a load flexibility of 77 GW of power and 90 GWh of virtual energy storage capacity nationwide (Kalsi, 2017). Therefore, some portion of the supply–demand imbalance can be met by these DERs at a lower cost compared to business-as-usual solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Machine learning for modern power distribution systems: Progress and perspectives

The application of machine learning (ML) to power and energy systems (PES) is being researched at an astounding rate, resulting in a significant number of recent additions to the literature. As the infrastructure of electric power systems evolves, so does interest in deploying ML techniques to PES. However, despite growing interest, the limited number of reported real-world applications suggests that the gap between research and practice is yet to be fully bridged. To help highlight areas where this gap could be narrowed, this article discusses the challenges and opportunities in developing and adapting ML techniques for modern electric power systems, with a particular focus on power distribution systems. These systems play a crucial role in transforming the electric power sector and accommodating emerging distributed technologies to mitigate the impacts of climate change and accelerate the transition to a sustainable energy future. The objective of this article is not to provide an exhaustive overview of the state-of-the-art in the literature, but rather to make the topic accessible to readers with an engineering or computer science background and an interest in the field of ML for PES, thereby encouraging cross-disciplinary research in this rapidly developing field. To this end, the article discusses the ways in which ML can contribute to addressing the evolving operational challenges facing power distribution systems and identifies relevant application areas that exemplify the potential for ML to make near-term contributions. At the same time, key considerations for the practical implementation of ML in power distribution systems are discussed, along with suggestions for several potential future directions.

Marković, Marija (ORCID:0000000247839837)↗

DOE OSTI2022

Decarbonization scenarios of the U.S. Electricity system and their costs

Decarbonizing the electricity system to zero-carbon emission is crucial for climate change mitigation. Previous studies have shown that such a transition in the United States (U.S.) may lead to higher system cost compared to a business-as-usual case, but it is not well-known how the cost of electricity generation varies at sub-regional level under the transition, and studies have rarely evaluated the trade-off between the cost and avoided climate damages, as well as the potential roles of negative emission technologies (NETs) in the electricity decarbonization. In this work, we present a regionally resolved national model to quantify the cost of decarbonizing the U.S. electricity system under a set of possible scenarios. The results show that, compared to the reference scenario without a decarbonization policy, reaching zero CO 2 emission by 2050 would incur, depending on the scenarios, 335-494 billion USD additional cost to the U.S. electric power sector during 2020-2050. The regional costs of electricity generation ranges from 2.4 to 4.7 cent/kWh, largely due to the generation profiles and renewable resources availability of those regions. The additional costs can be translated to an average CO 2 abatement cost of 29-59 USD/metric ton CO 2 (with 2%-7% discount rates), which are comparable to the social cost of carbon in the literature at around 4% discount rate. The results also show that the cost of mitigating the last few percent CO 2 emission from the U.S. electricity system may exceed the costs of NETs, indicating an opportunity for NETs to contribute to electricity decarbonization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Editorial: Advanced water splitting technologies development: Best practices and protocols

As the level of deployment and utilization of renewable energy sources, including wind and solar, continues to rise, large-scale, long-term energy storage technologies that could accommodate weekly and seasonal energy fluctuations will play a significant role in the overall deployment of renewable energies in the future. Harnessing and storing renewable energy resources via electrochemical, photoelectrochemical, or thermochemical processes by converting renewable energy into sustainable (energy storage) fuels have the potential to meet the long-term, terawatt scale energy storage challenge. Renewable hydrogen production is the cornerstone for sustainable fuel production and deep decarbonization of multiple sectors in our society. Cost-competitive clean hydrogen provides value to applications, such as 1) in the transportation sector for fuel cell vehicles, 2) in the electric grid sector for system stability and load balancing, and 3) in the industrial sector with metal refineries, cement production, and biomass upgrading (carbon-free fertilizer production). In addition, coupling clean renewable hydrogen with the carbon and nitrogen cycles enables known and well-established thermal-chemical processes to generate renewable hydrocarbon fuels and ammonia. The Advanced Water Splitting Technologies (AWST): low temperature electrolysis (LTE), high temperature electrolysis (HTE), photoelectrochemical (PEC) and solar thermo-chemical hydrogen (STCH) provide four unique and parallel approaches to produce low cost, low greenhouse gas (GHG) emission hydrogen at scale (Figure 1). Cost competitive clean hydrogen production using these four technologies is a current high priority focus for governments and industry. In June of 2022, the U.S. Department of Energy (DOE) launched the first in a series of Earthshot Initiatives. The Hydrogen Shot, “1 1 1” aims to reduce the cost of clean hydrogen by more than 80% to one dollar per one kilogram in 1 decade ($\$$1/kg H 2 ). The European Green Deal and the International Energy Agency (IEA) have implemented a strong focus on green hydrogen production for a clean and secure energy future.

benchmarking, low temperature electrolysis↗

DOE OSTI2024

Opportunities and Implications for Low-Cost Hydrogen Production from Water Electrolysis in a Decarbonizing Power Sector

Increased deployment of renewable power generation such as wind and solar photovoltaics along with electrification of transportation and other sectors are driving changes in the operation and economics of the electric power sector. Simultaneously, efforts to decarbonize other sectors of the economy such as steelmaking and heavy duty transportation will require significant amounts of electricity to drive electrons to molecules processes. Hydrogen production via water splitting electrolysis is a key near-term technology for decarbonization that interfaces between the power sector and decarbonization efforts in industrial sectors. This poster examines the implications for increased deployment of water electrolyzers in a rapidly evolving energy system. The economic opportunities for low-cost hydrogen production from electrolysis that are facilitated by highly renewable grids will be examined and discussed. Durability, cost, and operational strategies for electrolyzers interacting in these future energy systems are key to enabling hydrogen at scale. This poster will overview these considerations and ongoing work within the U.S. Department of Energy’s H2NEW consortium that is focused on addressing them.

electrolysis↗

DOE OSTI2020

Economic Analysis of Integrated Solar Power, Hydrogen Production, and Electricity Markets

Hydrogen is a versatile energy carrier that is used in a wide variety of chemical and industrial processes. Producing hydrogen using electrolysis can enable integration of multiple sectors including electricity, heating, and industrial sectors; however, the cost of producing hydrogen from electrolysis remains a challenge for encouraging greater adoption. To help improve the economics for both solar PV and hydrogen production using electrolyzers, we explore the benefit of combining PV and electrolysis systems. Using the Revenue Operation and Device Optimization Model (RODeO) model, the optimal breakeven hydrogen production cost for six unique market participation configurations is calculated at six candidate locations in California where PV is already installed. Costs include production, storage, and compression in preparation for gaseous delivery trucks. Revenue streams included in the optimization are the sale of hydrogen, Low Carbon Fuel Standard (LCFS) credits, renewable electricity sold to the grid, and Renewable Energy Credits (REC). The costs included are the electricity costs, capital and fixed operation and maintenance cost (FOM) for the electrolyzer, PV, and storage and compression systems as well as taxes and financing costs. In addition, cost reductions are achieved through retail and wholesale electricity use optimization, by which electricity is purchased at the lowest price and sold, if possible, at the highest price. For all locations analyzed, the breakeven hydrogen production cost results show that, in order of decreasing cost, the system configurations are islanded (highest), separated, NEM, retail, hybrid retail/wholesale, and wholesale (lowest). This report also explores other aspects of hydrogen systems including optimal renewable sizing and resulting energy mixture to the electrolyzer, value of renewable premiums, competition with incumbent technologies, cost sensitivity to a variety of parameters.

decarbonized economy↗

NASA NTRS1973

Observed relationships between electric fields and auroral particle precipitation.

Simultaneous electric field and plasma observations with the low-altitude polar-orbiting satellite Injun 5 have provided a comprehensive survey of convection electric fields and their association with magnetospheric plasma phenomena. The most prominent features of the convection electric fields are reversals located at high magnetic latitudes, with generally antisunward convection poleward and sunward convection equatorward of the electric field reversal location. The electric field reversal is interpreted as the boundary between open and closed magnetic field lines. During local day the electric field reversal is observed to coincide with the equatorward boundary of the polar cusp. The plasma flow in the dayside polar cusp region is dominantly E-W, away from the stagnation point, the convection velocities typically being about 1 km/sec. At local evening, 'inverted V' electron precipitation bands are observed near or at the position of the electric field reversal. In the local late-evening sector the electric field reversal becomes less distinct, and often no single well-defined electric field reversal can be identified. In all cases the inverted V electron precipitation events are closely associated with large, typically greater than 30 mV/m, irregular electric field fluctuations with time scales of a few seconds or less.

Gurnett, D. A.↗

DOE OSTI2022

interflow: A Python package to organize, calculate, and visualize sectoral interdependency flow data

Many economic sectors rely on an uninterrupted “upstream” supply of a resource to conduct their primary functions, leaving them vulnerable to adverse effects should that resource flow be interrupted or compromised (OECD, 2017; U.S. EPA, 2010). Well-known examples of these relationships include water demand by the energy sector (e.g., thermoelectric cooling for nuclear generation) (Grubert & Sanders, 2018; Webber, 2017) and energy demand by the water sector (e.g., electricity required to treat or move water in the public water sector) (Congressional Research Service, 2017) though many others exist. Being able to calculate and document these interdependencies and evaluate where the greatest cross-sectoral intensities and flows exist can reveal opportunities to enhance the overall network. Despite the implications and potential impacts, however, these interconnections and flows have been historically complex to analyze and understand. The interflow package provides a flexible tool to organize, calculate, and visualize (using Sankey diagrams and other visualizations) sectoral interdependency flows for multiple subsectors and resources. This tool can help decision-makers, researchers, and other audiences more easily pull meaning from these interdependencies to reveal multi-faceted opportunities and risks. interflow can help investigate questions such as (1) which sectors have high cross-resource dependencies, (2) how does demand for a resource in various sectors compare across regions, and (3) where the sectoral and regional opportunities are for enhanced efficiency, security, and resiliency.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Medium- and Heavy-Duty Vehicle Electrification: An Assessment of Technology and Knowledge Gaps

The objective of this assessment was to leverage current medium- and heavy-duty vehicle (MHDV) data and information to evaluate the state of commercial vehicle electrification technologies, including the following: 1. Assessment and inventory of current MHDV electrification architectures; 2. Identification and assessment of MHDV component technologies; 3. Assessment of potential performance and cost drivers; and, 4. Identification of R&D gaps where appropriate R&D and technology would accelerate commercial vehicle electrification. These gaps include shortfalls in technology, gaps in data, and inadequate knowledge and understanding. To inform this study, the National Renewable Energy Laboratory–Oak Ridge National Laboratory team examined the open literature; conducted workshops; assessed and analyzed data on more than 175 electrified MHDVs, including vehicle and powertrain specifications; and conducted one-on-one meetings with industry representatives. This systems-level information was concatenated and parsed with respect to key characteristics such as battery energy, power, and range compared across vehicle classes. Operational data of many conventional vehicles were also examined to help determine the requirements on electrified vehicle attributes such as range. Previous studies on the total cost of ownership of electrified MHDVs were reviewed to determine where improvements in technologies (efficiency, cost, maintenance) were needed to accelerate adoption. The team also assessed the state of the art in electric drivetrains for component specifications and challenges for the commercial vehicle sector, including electric machines, power electronics, and off-board high-power charging systems (extreme fast charging and beyond). The goal of this analysis was to identify the barriers to widespread adoption of commercial vehicle electrification technologies and prioritize the research and development gaps that need to be overcome to accelerate significant market penetration of these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Power Sector Decarbonization in South Asia: Pathways for Research, Modeling, and Implementation

Decarbonization of the power sector has far-reaching impact into the further decarbonization of the economy. In many comprehensive decarbonization pathways proposed for the world and for India electrification of transportation, buildings, and industry is the principal solution to decarbonizing those sectors. Therefore, electricity grids are likely to grow as more and new loads are added to them, and this growth will necessarily be from non-carbon emitting resources. This report outlines several key challenges for the power sector in planning, research, and development towards a decarbonized electric power grid. While these challenges will continue to evolve, this report focuses on formulating the important questions for the next two decades to align planning timeframes of India's and South Asia's power sector stakeholders, and to offer near-term research solutions for preparing the datasets, building the models, and designing the studies to answer questions and prepare for these changes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Industry Requirements for Geomagnetic Disturbance Models

This research project will address the most pressing uncertainties in modeling and measuring the electric power grid effects of geomagnetic disturbances (GMDs) and the E3 portion of nuclear electromagnetic pulse (EMP). The primary goal is to help decision-makers in the electric power sector have the knowledge and tools they need to most effectively mitigate GMD effects on our nation’s electric grid, with a secondary focus on EMP. Comprehensive modeling, model assessment through sensitivity analysis, and validation with field measurement data will be the primary tasks undertaken. The goal will be a more widespread adoption of these modeling approaches, namely characterizing the uncertainty associated with these models and how that uncertainty will affect decision-making by industry. This document summarizes industry requirements for better decision-making tools, informed by feedback from an industry advisory board. These requirements help guide planning and execution of the project's remaining tasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Probabilistic Impact Assessment and Software Tool Requirements

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Precursor Analysis Report: Industroyer Targeting Ukraine Electric Power Transport Utility (Ukrenergo) 2016

The Industroyer Targeting Ukraine Electric Power Transport Utility (Ukrenergo) 2016 Precursor Analysis Report leverages publicly available information about the December 2016 cyber attack against the Ukrainian Ukrenergo electric transmission utility and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. Industroyer is a modular malware framework designed to deploy several Industrial Control System (ICS) protocol-specific attack payloads to disrupt electricity distribution. Adversaries deployed Industroyer within the target network on a Microsoft Windows endpoint capable of directly manipulating or communicating with ICS. Industroyer abuses the functionality of a targeted ICS’s legitimate control system to achieve its intended impact. Adversaries likely first gained access to Ukrenergo enterprise networks in early 2016 after a successful spearphishing campaign against organizations in the electric power sector. Adversaries then began capturing credentials beginning on 1 December 2016. This allowed access to the ICS environment at the Pivnichna electric transmission substation outside Kyiv through a device dual-homed on the Information Technology (IT) and ICS networks. Adversaries conducted discovery, targeting, and access to this device using information and previously captured credentials from compromised enterprise IT machines. Finally, the adversaries deployed and launched the Industroyer malware just before midnight on 17 December. By midnight, Ukrenergo had lost control of a targeted substation, resulting in electric power outages for over an hour in the city of Kyiv and the Kyiv region. Researchers and analysts identified 31 unique techniques (used in a sequence of 33 steps) utilized during the attack with a total of 846 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Twenty-nine of the identified techniques used during the Industroyer cyber attack were precursors to the triggering event. Analysis identified 548 observables associated with these precursor techniques, 353 of which were assessed to have an increased likelihood of being perceived in the 300 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Tethys Water Demand Data

U.S. water demand varies sharply by sector and region as land use, population, weather patterns, and economic activity co-evolve. High-resolution water demand data is required to capture these dynamics, support integrated energy-water-land modeling, and local-to-regional water scarcity assessments. This dataset contains gridded (1/8 degree), monthly, multi-sector water demand dataset for the contiguous United States (CONUS) covering 1980-2100 across eight future scenarios of human-Earth system change. The dataset covers irrigation, thermoelectric, municipal (public-supply and domestic), livestock, manufacturing, and mining demands, separately for withdrawals and consumption, and includes per-cell renewable vs. non-renewable water source attributions. The dataset is validated against the latest USGS 2010-2020 water-use data for the three largest water demand sectors (Domestic, Electricity, and Irrigation), with correlations ranging from 0.73-0.95 at the HUC6 scale. The two datasets largely agree on an aggregate basis with per-sector bias falling within +/-7%, but they disagree on the spatial allocation of water with individual HUC6 basins having normalized RMSE from 68-171% and median absolute percent difference from 37-86%. This dataset advances prior global products by combining state-resolved sectoral demands from GCAM-USA, future power-plant siting from the CERF model, and scenario-consistent high-resolution climate and population forcing data across the eight scenarios.

GCAM-USA↗