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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evolution of Plug-In Electric Vehicle Charging Infrastructure in the United States: Preprint

The U.S. Department of Energy’s Alternative Fuels Data Center (AFDC) has tracked alternative fueling and electric vehicle charging infrastructure in the United States since 1991. This paper explores the history of the AFDC Station Locator, which was launched in 1999, and discusses the growth of electric vehicle supply equipment. It also looks at how electric vehicle drivers access public charging, and evaluates challenges, gaps, and opportunities facing both electric vehicle drivers and the industry as a whole.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI-XFC)

Increasing vehicle electrification will require extensive use of extreme fast charging (XFC), especially for larger vehicles. Uncoordinated XFC can create grid challenges, particularly at the distribution level. Two strategies can support widespread XFC: gold-plate the grid (i.e., upgrade all systems to enable worst-case, fully coincident loads) or use integrated planning to codesign a smart system based on advanced controls that leverage load flexibility and distributed energy resources. With the right design and control, XFC can simultaneously support both mobility and grid operations. Fully realizing the potential of XFC, however, will require unprecedented coordination among the charging infrastructure, grid, and vehicles. GEMINI-XFC combines high-fidelity grid and transport modeling at an unprecedented level of resolution and codesigns a smart system based on advanced controls that leverage load flexibility and distributed energy resources to optimize the integration of extreme fast charging (XFC) across a full regional scale with individual customer resolution.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Technology Validation of Hydrogen Refueling Infrastructure

NREL presented results from hydrogen refueling infrastructure evaluations by the National Fuel Cell Technology Evaluation Center, including current status of hydrogen fueling stations, what fuel cell electric vehicle owners can expect when using stations, cost to station operators and customers, and reliability of hydrogen stations.

39 EE - Hydrogen and Fuel Cell Technologies (EE-3F↗
DOE OSTI2021

Electric Vehicle Infrastructure Projection Tool (EVI-Pro)

This presentation includes results from the second California installment of EVI-Pro. Pursuant to California Assembly Bill 2127, evolving market and technology conditions warrant updating this statewide infrastructure assessment at least every two years. EVI-Pro has been updated to consider California's 2030 goal to have 5 million zero emission vehicles (ZEVs) on the road by 2030. CEC and NREL with the support of UC Davis and other state agencies, have set out to refine EVI-Pro to reflect increasing PEV market share, evolving vehicle and charging technology, and observed charging behavior.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗
DOE OSTI2021

Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) Research: Controls

Advanced Turbine Control for Distributed Wind Deployments: The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) research initiative is funded by the U.S. Department of Energy’s Wind Energy Technologies Office and led by researchers at the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories (Sandia). The initiative’s controls research seeks to expand the benefits from distributed wind energy assets beyond solely providing low-cost power directly to consumers. To make these turbines operate more effectively, there is a need for more advanced ways to control them—allowing power companies, businesses, and energy consumers to take advantage of some of the unique technical characteristics of wind energy.

wind, Microgrids, Infrastructure, Resilience, Adva↗
DOE OSTI2022

Airport Infrastructure Expansion Under Uncertainty

Multistage stochastic optimization can help transportation hubs like airports and seaports plan for future infrastructure expansion while considering risks from emerging technologies and changes in demand.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data: Preprint

Many distribution network monitoring and control applications - including state estimation, volt/VAR optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure↗
DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data

Many distribution network monitoring and control applications - including state estimation, Volt/VAr optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder-head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure (AMI)↗
DOE OSTI2021

University Research Reactor & Infrastructure Awards

Presentation covering the FY2021 University Scientific Infrastructure funding program and the NSUF role in administering it. To be presented at the Nuclear Science User Facilities (NSUF) annual program review on November 9, 2021.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Community Engagement Tips for EV Infrastructure Deployment

This Joint Office of Energy and Transportation help sheet provides tips for conducting community engagement to support electric vehicle (EV) infrastructure planning and deployment. This document is a tool and an informative resource to be used in conjunction with other guidance. It is not intended to set policy or establish or replace any standards under state or federal law applicable to public notice or community engagement.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗
DOE OSTI2024

2024 Sustainable Aviation Energy Conference: 5 Key Messages From the Alternative Fueling (Energy) Infrastructure Workshop

At the 2024 Sustainable Aviation Energy Conference, more than 100 aviation leaders gathered in Dallas, Texas, to discuss collaboration and research needed to clear the path to widespread adoption of sustainable aviation technologies. During open workshops, participants from state and federal agencies; airports; aircraft and engine manufacturers; liquid fuel producers; and other stakeholder groups brainstormed the biggest barriers and opportunities for realizing a sustainable aviation ecosystem. This fact sheets presents five key messages and discussion points that emerged during a workshop on alternative fueling (energy) infrastructure.

advanced air mobility↗
DOE OSTI2024

Data Analytics and Visualization of Energy Systems for Critical Infrastructure Insights

Modernization of energy systems including transportation facilities provides opportunities for increased efficiency, expansion of commerce and meeting industry and federal goals. A significant increase in electrical demand is projected to meet these needs, which concentrates at facilities such as airports. For example, Xcel Energy working with two airports in their service area recently published information projecting an up to fivefold increase in electricity demand in the next 25 years [1]. Concurrently, the US Government Accountability Office (GAO) recently surveyed 30 commercial service airports identifying more than 300 outages of more than 5 minutes between 2015 and 2022 [2]. Power, reliability, and resilience planning becomes more important to safely maintain operations and the flow of commerce with fewer energy carriers providing necessary energy to safely move passengers and goods. NREL proposes to develop methodologies to allow owners, utilities, and federal agencies to dynamically analyze, forecast, and manage energy loads at airports, focused upon maintaining the flow of commerce in an efficient, sustainable, and resilient way. To address these energy challenges, a suite of technologies and methodologies can be leveraged to validate concepts, inform design, de-risk solutions and optimize energy management during deployment. These technologies include digitalization of energy systems, microgrid methodologies, and related energy technologies for building and vehicle loads. [1] Electrifying Airport Ecosystems - https://www.enterprisemobility.com/content/dam/enterpriseholdings/marketing/innovation-in-mobility/vehicle-innovation/airport-electrification-study-full-report-2024.pdf [2] Airport Infrastructure: Selected Airport's Efforts to Enhance Electrical Resilience https://www.gao.gov/products/gao-23-105203.

critcal infrastructure↗
DOE OSTI2024

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential While Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics: Preprint

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗
DOE OSTI2024

Dover CoreGuard Ⓡ Cybersecurity Protections for Critical Energy Infrastructure Final Report

This report documents the status of technical objectives and activities for the Department of Energy (DOE) Small Business Innovation Research (SBIR) Phase I project, titled “Dover CoreGuard Ⓡ Cybersecurity Protections for Critical Energy Infrastructure” (Award No. DE-SC0023743), undertaken by Dover Microsystems, Inc., Wayland, MA. The Principal Investigator for this project was Dr. Stephen Papa, Dover’s Chief Technology Officer (CTO). The contract PoP (Period of Performance) is scheduled for completion by February 9, 2024.

99 GENERAL AND MISCELLANEOUS↗