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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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DOE OSTI2026

SCRES Energy Quest Workshop (Technical Report)

Energy Quest: Sitka’s Path to 2050 is a game based public engagement tool developed as part of the Sitka Community Renewable Energy Strategy and the U.S. Department of Energy’s Energy Transitions Initiative Partnership Project Cohort 3. Designed for Sitka’s isolated island microgrid, which is powered primarily by hydropower and depends on imported diesel for backup, the game translated complex long term energy planning questions into an interactive format. In facilitated workshops, residents built energy roadmaps to 2050, explored tradeoffs, and expressed priorities around four themes: affordability, reliability, self sufficiency, and innovation. Across sessions, participants showed strong support for increasing local self sufficiency and resilience, even when this required balancing near term affordability with long term investments. They emphasized reducing dependence on imported diesel, making better use of existing hydropower, and considering new renewable generation such as solar, wind, and additional hydropower. Survey and game responses also highlighted interest in using surplus hydropower to support new industries, expanding electrification of heating and transportation, and exploring emerging technologies and green fuels. The report organizes these findings into four scenario themes to guide Sitka’s 2050 energy planning. Affordability focuses on managing rate impacts, efficiency, and conservation. Reliability addresses diversified generation, backup power, and energy security. Self sufficiency emphasizes distributed generation and reduced reliance on imported fuels. Innovation explores new technologies, marine based energy solutions, and low carbon fuels. By grounding future planning in these community derived themes, Energy Quest shows how a game based approach can make technical energy planning more accessible and inclusive for remote communities. For questions about the game board and piece production email Dr. Sarah Troise (sarah.troise@pnnl.gov)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Impact of Open Communication Networks on Load Frequency Control with Plug-in Electric Vehicles by Cyber-Physical Dynamic Co-Simulation: Preprint

With the increasing electrification of the transportation sector, vehicle to grid (V2G) control technologies are promising to improving system frequency stability. However, these control technologies might require non-traditional communication supports. This paper investigates the impacts of electric vehicles (EVs) V2G on power system frequency regulation considering communication variations through transmission-distribution-communication (TDC) dynamic simulation. The simulation model is built based on our previously developed open-source transmission-and-distribution (T&D) dynamic co-simulation framework. Here, we add the communication variation functions (i.e. delay and packet loss) to complete the TDC simulation framework. In the case studies, practical communication variation scenarios are considered when the system experiencing an N-1 generation trip contingency. The considered scenarios include communication delay and packet loss using both homogeneous and heterogeneous assumptions. The delay and packet loss rate are the same in all communication channels in the homogeneous case but varies in the heterogeneous case. The results show the communication delay has an obvious impact on the frequency recovery compared to the communication packet drop. The impacts of the standard deviations of communication delay time and packet drop rate are not significant. The outcomes of this work can help improve the EV frequency regulation services and provide robust and effect supports to the grid.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

EVI-X Updates and National Charging Assessment Report

With the support of DOE's Vehicle Technologies Office and the DOE/DOT Joint Office (JO), NREL has applied the EVI-X modeling suite to conduct a National Electric Vehicle Infrastructure Needs Assessment. This report considers a 2030 scenario in which 30-42 million light-duty electric vehicles are on the road (including plug-in hybrids). We consider the needs of vehicles used for typical daily driving, drivers without access to residential charging, corridor charging supporting long-distance travel, and ride-hailing electrification. We find that a national network of 28 million charging ports (including public and private infrastructure) will be necessary in our mid adoption scenario. This result is framed as a conservative estimate as the assumed costs include charging equipment and installation but exclude the cost of grid upgrades and distributed energy resources.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Disaggregating Future Retail Electricity Rate Growth [Slides]

Recent Berkeley Lab research found that modest retail rate increases over the past 10 years were mostly driven by large increases in capital expenditures (CapEx) that were offset in part by substantial wholesale price reductions. Decision-makers are increasingly concerned about the potential future rate impacts of a number of policies and industry trends that support rapid decarbonization, electrification, and grid modernization. Using historical FERC Form 1 data and the existing literature on policies and industry trends that are likely to affect utility-incurred costs and retail sales, Berkeley Lab researchers developed ranges of forecasted growth rates for cost-related rate drivers (i.e., fuel and purchased power; transmission, distribution, generation, and other categories of both non-fuel operations & maintenance and CapEx) and non-cost related rate drivers (i.e., retail sales, peak demand, and customers). These were then used as inputs to a pro-forma utility financial model (FINDER) that estimated the growth in retail electric rates between 2020 and 2030 for a prototypical vertically-integrated investor-owned utility in the United States. The analysis produced the following results: 1. Assuming average growth rates in all rate drivers, future retail rate growth is driven by sizable increases in all CapEx costs, where fuel and purchased power costs are replaced by generation CapEx as the largest rate component between 2020 and 2030. 2. Growth in sales/peak demand/customers, generation CapEx costs, and fuel and purchased power (FPP) costs, in isolation, produce the most uncertainty in rate growth. Specifically, a 1% increase in the compound annual growth rate (CAGR) of retail sales, coincident peak demand (CP), and customers (Sales-CP-Cust) results in a 0.88-0.93% decrease in the CAGR of rates, in isolation. However, a 1% increase in the CAGR of generation CapEx budgets results in a 0.07-0.14% increase in the CAGR of rates, while a 1% increase in the CAGR of FPP costs causes a 0.10-0.14% increase in the CAGR of rates, all else being equal. 3. Taking into account the correlation and variability of the growth in all rate drivers jointly, generation CapEx is expected to be both the largest and most uncertain rate component by 2030 (20-25% share of the retail rate). Transmission and distribution CapEx, along with fuel and purchased power costs are each expected to comprise between 12% and 17% of retail rates.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Electrification 2022 Annual Progress Report

The Electric Drive Technologies (EDT) program's mission is to conduct early-stage research and development on transportation electrification technologies that accelerate the development of cost-effective and compact electric traction drive systems that meet or exceed performance and reliability requirements of internal combustion engine (ICE)-based vehicles, thereby enabling electrification across all light-duty vehicle types. The Grid and Charging Infrastructure (G&I) program's mission is to conduct early-stage research and development on transportation electrification technologies that enable reduced petroleum consumption by light, medium, and heavy-duty vehicles. The program identifies and enables the role of vehicles in the future electrical grid.

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DOE OSTI2024

Electrification (2023 Annual Progress Report)

This document summarizes the progress of VTO Electrification R&D projects supported during the fiscal year 2023. The Electric Drive Technologies (EDT) program’s mission is to conduct early-stage research and development on transportation electrification technologies that accelerate the development of cost-effective and compact electric traction drive systems that meet or exceed performance and reliability requirements of internal combustion engine (ICE)-based vehicles, thereby enabling electrification across all light-duty vehicle types. The Grid and Charging Infrastructure (G&I) program's mission is to conduct early-stage research and development on transportation electrification technologies that enable reduced petroleum consumption by light, medium, and heavy-duty vehicles. The program identifies and enables the role of vehicles in the future electrical grid.

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DOE OSTI2023

EV charging site day-ahead load prediction in a synthetic environment for RL based grid-informed charging

Ensuring grid health in the face of increasing demand for power is an emerging challenge especially due to transportation electrification. A free market approach to influencing electric vehicle (EV) load through grid-informed hourly dynamic pricing is introduced in this work. The setting of charging price is done by a reinforcement learning (RL) agent that learns the complicated dynamics by interacting with a synthetic environment. This synthetic environment is a combination of distribution feeder simulation, EV charger user behavior dynamics, and EV charging simulation. A key module in this synthetic environment involves obtaining the day-ahead charging profile of EV charging stations based on real-world past data. The day-ahead prediction is also useful in other traditional optimizations related to EV charge scheduling. The proposed approach involves using EV charging data from two different past time horizons – one to determine the shape of the daily profile and the other to determine a scaling value to capture actual energy consumption. Real-world charging data over many years from the ACN charging network has been used to demonstrate the ability to predict the day-ahead profile with only charge session data. Both Python and MATLAB have been used for data cleaning, processing, analysis, and prediction.

Suryanarayana, Harish↗
DOE OSTI2018

The Demand-Side Grid (dsgrid) Model Documentation

Electrical load is the backdrop for all power systems analysis. As a coequal partner in the supply-demand balance that must be maintained on electrical grids at all times and for all timescales, load is a major source of variability and uncertainty in grid operations. Despite this, utility load forecasting is typically done in a top-down manner that lacks the granularity in time, geography, end use, and technology that is needed to explore the potential impact of technological shifts; and many studies of future grid systems employ relatively simple scaling of historical loads, placing more emphasis on supply-side resources such as generation and transmission that are fewer in number and are better understood in terms of cost and performance. The primary purpose of the demand-side grid model (dsgrid) is to fill these gaps by creating comprehensive load data sets at a sufficient temporal, geographic, sectoral, and end-use resolution to enable detailed analyses of current patterns and future projections of end-use load. Furthermore, the dsgrid platform uses a bottom-up methodology that allows highly resolved analysis of 'what-if' scenarios. dsgrid leverages detailed sectoral energy models to provide hourly time series of load by subsector, end use, and county covering a full year. Although dsgrid currently emphasizes electricity load data, its component sector models for residential buildings, commercial buildings, and industry provide information on other fuel use, including natural gas. The data sets can thus be leveraged to support analysis of numerous demand-side technology-driven changes, such as energy efficiency, electrification, and operational flexibility (i.e., demand response). The electricity use data are time-synchronized with solar and wind data sets so as to be suitable for use in power systems analysis. This report documents dsgrid and its initial data set, which covers electricity demand in the contiguous United States for the historical year of 2012. We start with a historical year to enable model calibration and validation, as well as the development of a mathematical description of our model residuals that can be applied to future-year 'what-if' scenarios to remove known errors between our bottom-up modeling and historical load shapes. This work is part of the Electrification Futures Study (EFS), for which the dsgrid team will be developing future load snapshots that describe projected year 2050 under baseline and a range of electrification assumptions.

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DOE OSTI2024

Navigating Options for Transportation Electrification and Solar Charging: Steps and Lessons Learned in Montana Communities

This document is intended to assist communities who are considering investing in electric transportation. It can assist communities engage stakeholders, prioritize community goals, assess electric transportation options, and navigate complex decisions about deploying zero emission electric transportation in their community. It covers technological, economic and environmental aspects of the transition to electric vehicles (EV), and highlights the specific considerations related to the deployment of renewable energy technologies (e.g., distributed solar) in combination with EV supply equipment (EVSE, e.g., charging stations). There are many important decisions to make and questions for communities to ask themselves as they consider electric vehicle types, charging infrastructure, and electricity generation options. This guide will help communities assess: (1) Which stage in the decision-making process they are in with respect to EV deployment; (2) Questions they can explore to guide their decisions about EV deployment; (3) How to engage key stakeholders on EV deployment options; (4) Tradeoffs and benefits of various electric transportation options and; (5) Synergies of pairing electric vehicle charging and renewable energy generation technologies. The analysis and lessons learned presented in this roadmap are intended to serve as a template and guide for similarly situated communities across the country who want to prepare for and play a role in the electrified transportation future.

14 SOLAR ENERGY↗
DOE OSTI2018

FY2017 Electrification Annual Progress Report

During fiscal year 2017 (FY 2017), the U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO) funded early stage research & development (R&D) projects that address Batteries and Electrification of the U.S. transportation sector. The VTO Electrification Sub-Program is composed of Electric Drive Technologies, and Grid Integration activities. The Electric Drive Technologies group conducts R&D projects that advance Electric Motors and Power Electronics technologies. The Grid and Charging Infrastructure group conducts R&D projects that advance Grid Modernization and Electric Vehicle Charging technologies. This document presents a brief overview of the Electrification Sub-Program and progress reports for its R&D projects. Each of the progress reports provide a project overview and highlights of the technical results that were accomplished in FY 2017.

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DOE OSTI2022

Feasibility Study of Real-Time Carbon Emission Responsive Electric Vehicle Charging Control in Buildings: Preprint

With the progressing electrification of the transportation sector, the source of carbon emissions is gradually shifting from fossil fuel to grid electricity because of electric vehicles (EVs). The carbon intensity of the grid can fluctuate significantly within hours due to the time-varying power generation mix. Therefore, shifting EV charging loads to cleaner hours in response to the carbon intensity signals can reduce carbon emissions. Existing EV charging control methods typically consider the electricity price or the available generation by distributed energy resources (e.g., photovoltaics) to inform decision-making. Such methods tend to reduce energy costs but may neglect the environmental impact of EV charging activities. We propose and compare four carbon emission responsive EV charging controllers with various control rules. The proposed controllers are evaluated based on simulation experiments using metrics such as carbon emission reduction potential, state of charge (SOC) at departure, and peak demand. We found that the need of EV owners to have full batteries at departure could lead to an emission increase when the curtailed EV charge was compensated before departure. Further, up to 12.7% of carbon emission reduction can be achieved if the EV owners reduce the target SOC at departure by less than 15%.

carbon emission↗
DOE OSTI2019

Electrification 2018 Annual Progress Report

During fiscal year 2018 (FY 2018), the U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO) funded early stage research & development (R&D) projects that address batteries and electrification of the U.S. transportation sector. The VTO Electrification Sub-Program is composed of Electric Drive Technologies, and Grid Integration activities. The Electric Drive Technologies group conducts R&D projects that advance electric motors and power electronics technologies. The Grid and Charging Infrastructure group conducts R&D projects that advance grid modernization and electric vehicle charging technologies. This document presents a brief overview of the Electrification Sub-Program and progress reports for its R&D projects. Each of the progress reports provide a project overview and highlights of the technical results that were accomplished in FY 2018.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

An Electrified Nation: A Review of Study Scenarios and Future Analysis Needs for the United States

Historically, the term electrification has meant providing electricity to customers who lack access to electric infrastructure. From the earliest urban electric services in the 1890s to the electrification era in rural America from the 1930s to the 1950s, access to electricity drastically improved quality of life, including thermal comfort, hygiene, food availability, illumination, mobility, commerce, communication, and entertainment. As a result of these early electrification efforts, almost all U.S. homes are fully or partially electrified, with notable exceptions in some Native American and Alaska Native communities.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure

With the support of DOE's Vehicle Technologies Office and the DOE/DOT Joint Office (JO), NREL has applied the EVI-X modeling suite to conduct a National Electric Vehicle Infrastructure Needs Assessment. This report considers a 2030 scenario in which 50% of light-duty sales are electric (including plug-in hybrids), resulting in an on-road stock of 33 million vehicles. We consider the needs of vehicles used for typical daily driving, drivers without access to residential charging, corridor charging supporting long-distance travel, and ride-hailing electrification. We find that a cumulative capital investment of $82 billion in public and private charging infrastructure will be necessary in our baseline scenario (approximately 3x greater than our estimate of planned investments to date). This result is framed as a conservative estimate as the assumed costs include charging equipment and installation but exclude the cost of grid upgrades and distributed energy resources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Modeling U.S. Light-Duty Demand for EV Charging Infrastructure in 2030

With the support of DOE's Vehicle Technologies Office and the DOE/DOT Joint Office (JO), NREL has applied the EVI-X modeling suite to conduct a National Electric Vehicle Infrastructure Needs Assessment. This report considers a 2030 scenario in which 50% of light-duty sales are electric (including plug-in hybrids), resulting in an on-road stock of 33 million vehicles. We consider the needs of vehicles used for typical daily driving, drivers without access to residential charging, corridor charging supporting long-distance travel, and ride-hailing electrification. We find that a cumulative capital investment of $82 billion in public and private charging infrastructure will be necessary in our baseline scenario (approximately 3x greater than our estimate of planned investments to date). This result is framed as a conservative estimate as the assumed costs include charging equipment and installation but exclude the cost of grid upgrades and distributed energy resources.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1992

An intracloud lightning parameterization scheme for a storm electrification model

The parameterization of an intracloud lightning discharge has been implemented in the present storm electrification model. The initiation, propagation direction, and termination of the discharge are computed using the magnitude and direction of the electric field vector as the determining criteria. The charge redistribution due to the lightning is approximated assuming the channel to be an isolated conductor with zero net charge over its entire length. Various simulations involving differing amounts of charge transferred and distribution of charges have been done. Values of charge transfer, dipole moment change, and electrical energy dissipation computed in the model are consistent with observations. The effects of the lightning-produced ions on the hydrometeor charges and electric field components depend strongly on the amount of charge transferred. A comparison between the measured electric field change of an actual intracloud flash and the field change due to the simulated discharge shows favorable agreement. Limitations of the parameterization scheme are discussed.

Helsdon, John H., Jr.↗
DOE OSTI2024

Electric Medium- and Heavy-Duty Vehicle Charging Infrastructure Attributes and Development

Although more established for light-duty vehicles (LDVs), advancements in electric vehicle (EV) charging technology are being made in the medium- and heavy-duty (MD/HD) sector. Progress is also being made with the electrification of MD/HD vehicles, including transit buses, school buses, MD trucks, and HD trucks. The diverse set of operational requirements and duty cycles for each vocation, as well as the range in the size of fleets, present unique charging and infrastructure requirements. This report focuses on charging requirements for MD/HD vehicles and synergies with LDV infrastructure. This analysis leans toward the qualitative rather than quantitative because relevant model inputs are in development and will not be established for a few years, as EV deployments are more mature in the LDV sectors than MD/HD. The report begins with an overview of MD/HD vehicle classes and types of charging, including depot and residential charging, among others (Section 2). Section 3 analyzes the home bases (overnight dwell locations) of existing MD/HD vehicles, with an emphasis on depot and residential home bases, and discusses implications for charging infrastructure. Section 4 discusses the key characteristics for determining if, when, and where MD/HD vehicles can leverage LDV charging infrastructure rather than requiring dedicated chargers. These considerations include electricity demand, connectors, physical space requirements, payment considerations, and impacts on the grid. Section 5 summarizes shared characteristics for MD/HD vehicles that are appropriate for near-term electrification and includes a summary of the outlook of the electric MD/HD vehicle market. The conclusion (Section 6) summarizes the report's findings and outlines areas for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗