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At least 91 records · Page 5

Hourly Load Profile Dataset for Electric Transit Bus Depots in the United States

Transit buses operate primarily in dense urban areas, where nearby populations face increased exposure to fine particulates, nitrogen oxides, and other harmful pollutants. Electrifying transit buses presents a clear opportunity to reduce greenhouse gas emissions and improve urban air quality. However, widespread adoption may pose significant energy and infrastructure challenges, which can be mitigated through proactive planning and investment. This report presents a robust modeling framework and an initial estimation of the hourly electricity demand at transit bus depots across the United States. The resulting depot-level dataset, available at data.nrel.gov/submissions/282, provides valuable insights for infrastructure planning and electricity demand forecasting, supporting the scalable electrification of transit bus fleets nationwide.

33 ADVANCED PROPULSION SYSTEMS↗

Los Angeles Air Force Base Vehicle-to-Grid Demonstration (Final Project Report)

Electrification of non-tactical vehicle fleets represents a key efficiency and energy security objective for the United States Department of Defense. To achieve electrification, the department targeted vehicle-to-grid services as a way to decrease the overall cost of operating the vehicle fleet and achieve rough parity with traditional internal combustion engine vehicle fleets. This report describes efforts to aggregate a fleet of bi-directional electric vehicles and charging stations to provide regulation up and regulation down in the California Independent System Operator ancillary services market. A 29-vehicle electric vehicle demonstration fleet, consisting of mixed purpose and duty vehicles such as sedans, pickups, vans, and medium-duty trucks, was deployed at the Los Angeles Air Force base. The fleet provided frequency regulation to the California Independent System Operator’s wholesale electricity market to determine the capability of recouping some of the additional costs of procuring electric vehicles and their supporting infrastructure. Lawrence Berkeley National Laboratory, with its partner Kisensum, LLC, developed the fleet scheduling, optimization, and control software to allow the vehicle fleet at the air force base to participate in the ancillary services markets. This report focuses on the control software and market interactions, the significant challenges faced and solutions devised to address them, and examines the potential of using the electric vehicle fleet as an energy storage resource for the base buildings, an application known as vehicle-tobuilding, in providing demand response and emergency backup power. The report discusses key findings related to providing frequency regulation to the California Independent System Operator market, electric vehicle fleet performance, compatibility of varying resource parameters of vehicle fleet aggregation, the need for automated methods for communicating hour-ahead energy bidding, challenges related to battery capacity and charge/discharge rates, and monthly settlement revenue.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Shorepower Truck Electrification Project (STEP) - 1Q - 2Q 2013

The Fleet Test and Evaluation Team at the U.S. Department of Energy's National Renewable Energy Laboratory is evaluating and documenting the use of shorepower at 50 planned American Recovery and Reinvestment Act (ARRA)-funded truck stop electrification (TSE) sites across the nation. Trucks participating in the study have idle-reduction equipment installed that was purchased with rebates through the ARRA. A total of 5,000 rebates will be approved. the ARRA. A total of 5,000 rebates will be approved.

33 ADVANCED PROPULSION SYSTEMS↗

Shorepower Truck Electrification Project (STEP) - 2013 (Fact Sheet)

The Fleet Test and Evaluation Team at the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is evaluating and documenting the use of shorepower at 50 planned American Recovery and Reinvestment Act (ARRA)-funded truck stop electrification sites across the nation. Trucks participating in the study have idle-reduction equipment installed that was purchased with rebates through the ARRA. A total of 5,000 rebates will be approved.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quick Start to Electrifying Your School Bus Fleet

Learn how electric school buses can work for your district by understanding the basics of electrification. Understand what is needed to electrify your fleet, how much it costs, and how the process will effect your greenhouse gas emission impacts.

ADVANCED PROPULSION SYSTEMS↗

Transportation Electrification Beyond Light Duty: Technology and Market Assessment

Commercial fleets form the backbone of the nation’s economy, getting people and the things they need to the places they need to go and performing services necessary to keep public and private physical infrastructure in working order. Commercial fleets include a wide range of vehicle and equipment types, typical uses, and sizes, and involve millions of on-road and offroad vehicles. This diversity means there is no single solution to the challenges these vehicles pose for reducing petroleum dependence, impact on air quality, and emission of greenhouse gases. This document focuses on electrification of government, commercial, and industrial fleets. These fleets have been divided into three market segments based on equipment use: service fleets, goods movement, and people movement. In particular, it addresses highway vehicles not used for personal transport; non-highway modes, including air, rail, and water; and non-road equipment used directly or in support of these uses.

33 ADVANCED PROPULSION SYSTEMS↗

Energy consumption and charging load profiles from long-haul truck electrification in the United States

Abstract The urgent need to decarbonize the transportation sector combined with falling battery prices has spurred industry and policy interest in long-haul truck electrification. The charging behavior and resulting loads from electrified long-haul freight trucks are crucial for the smooth operation of the electric grid and have far-reaching environmental impacts (e.g., greenhouse gas and other air pollutant emissions). However, the aggregate energy impact of a fleetwide shift to electrified long-haul freight trucking has not been explored. This study combines electric truck design scenarios, bottom-up truck weight modeling, vehicle energy modeling, large-scale truck traffic data, and simulation of likely operation and charging behaviors to estimate end-use energy consumption and location-specific hourly charging loads for a national fleet of long-haul electric trucks. Relative to a fleet of future diesel trucks, electrification would reduce direct end-use energy consumption by 0.9 × 10 18 J (0.9 quadrillion BTU), but electrification might increase life cycle energy consumption depending on the electricity source. The electricity required to charge long-haul electric trucks is equivalent to five percent of annual electricity consumption in the United States (US). The simulated truck charging loads peak during the day across the US grid regions, but the charging peaks’ exact timing is sensitive to when trucks are dispatched for operation. The load shapes suggest that electric trucks’ charging loads can coincide with peaks in solar power generation, and planning could enable on- or off-site integration between truck charging stations and renewable electricity generation.

Tong, Fan (ORCID:0000000346613956)↗

Shorepower Truck Electrification Project (STEP) - Cumulative through February 2015

The Fleet Test and Evaluation Team at the U.S. Department of Energy's National Renewable Energy Laboratory is evaluating and documenting the use of shorepower at 50 planned American Recovery and Reinvestment Act (ARRA)-funded truck stop electrification sites across the nation. Trucks participating in the study have idle-reduction equipment installed that was purchased with rebates through the ARRA. A total of 5,000 rebates will be approved.

33 ADVANCED PROPULSION SYSTEMS↗

Shorepower Truck Electrification Project (STEP) - Cumulative through June 2014

The Fleet Test and Evaluation Team at the U.S. Department of Energy's National Renewable Energy Laboratory is evaluating and documenting the use of shorepower at 50 planned American Recovery and Reinvestment Act (ARRA)-funded truck stop electrification (TSE) sites across the nation. Trucks participating in the study have idle-reduction equipment installed that was purchased with rebates through the ARRA. A total of 5,000 rebates will be approved.

33 ADVANCED PROPULSION SYSTEMS↗

Development of a DC Fast Charging Station Model for Use with EV Infrastructure Projection Tool

The deployment of public charging infrastructure networks has been a major factor in enabling electric vehicle (EV) technology transition, and must continue to support the adoption of this technology. DC fast charging (DCFC) increases customer convenience by lowering charging time, enables long-distance EV travel, and could allow the electrification of high-mileage fleets. Yet, high capital costs and uneven power demand have been major challenges to the widespread deployment of DCFC stations. There is a need to better understand DCFC stations' loading, utilization, and customer service quality (i.e. queuing time, charging duration, and queue length). This study aims to analyze these aspects using one million vehicle-days of travel data within the Columbus, OH, region. Monte Carlo analysis is carried out in three types of areas - urban, suburban, and rural- to quantify the effect of uncertain parameters on DCFC station loading and service quality.

25 ENERGY STORAGE↗

Modeling and Analysis of a Fast Charging Station and Evaluation of Service Quality for Electric Vehicles

The deployment of public charging infrastructure networks has been a major factor in enabling electric vehicle (EV) technology transition and must continue to support the adoption of this technology. DC fast charging (DCFC) increases customer convenience by lowering charging time, enables long-distance EV travel, and could allow the electrification of high-mileage fleets. Yet, high capital costs and uneven power demand have been major challenges to the widespread deployment of DCFC stations. There is a need to better understand DCFC stations' loading and customer service quality. Furthermore, the relationship between the initial investment decision on building certain number of ports and customer satisfaction should be quantified. This paper aims to analyze these aspects using one million vehicle days of travel data within the Columbus, OH, USA, region. Monte Carlo analysis is carried out in three types of areas - urban, suburban, and rural - to quantify the effect of uncertain parameters on DCFC station loading and service quality. Additional simulations based on a homogeneous vehicle population are carried out, and closed-form equations are derived therefrom to estimate charging duration and waiting time in the queue. Optimization of DCFC station design is also addressed through the number and capacity of ports.

33 ADVANCED PROPULSION SYSTEMS↗

EVs@Scale Next-Gen Profiles - Fleet Utilization 2023

As U.S. fleet operators begin transitioning to electric vehicles (EVs), critical questions arise regarding how to manage this shift without disrupting fleet operations or placing undue stress on the electric grid. A major challenge for fleets is maintaining effective operational schedules while accommodating charging requirements, particularly with high-power charging (HPC) infrastructure, which presents grid stability concerns for utilities. Proposed solutions such as charging substations, megawatt charging systems (MCS), and smart charge management systems (SCMS) offer potential pathways forward, but their effectiveness depends on alignment with real-world fleet behavior and operational constraints. This report investigates the charging and utilization behavior of EV and EVSE fleets actively employing HPC technologies by conducting detailed case study analyses based on telematics data. A suite of predefined metrics—covering charging, routing, and other operational behaviors—is developed to evaluate the impact of fleet activities on grid infrastructure and identify opportunities for optimization. Results highlight variations in charging behavior across fleets, such as weekday versus weekend usage, diurnal charging trends, and the role of operational predictability in enabling SCMS effectiveness. While SCMS can help lower costs and improve energy efficiency for fleets with stable schedules, they may be insufficient for fleets with highly variable or long-haul operations, which may require more robust solutions like MCS. Visualization of aggregated hourly energy metrics reveals that while fleet behaviors are diverse, there are common temporal patterns that could inform infrastructure planning and energy management. These insights emphasize the need for fleet-specific charging strategies that minimize grid impact while supporting reliable fleet operations. Additionally, the report underscores the broader economic stakes of electrification, particularly in high-value markets such as freight, where misaligned transitions could stall EV adoption. By examining current EV and EVSE fleet deployments using predetermined standardized metrics, this study offers a foundation for developing technologies and operational frameworks that support scalable, grid-compatible electrification across a variety of fleet types while establishing a baseline understanding of operational behaviors. In doing so, we aim to ensure that future charging solutions reflect actual fleet needs and grid constraints—an essential step toward maintaining operational continuity and achieving a successful transition to electric fleet operations.

Charging↗

Estimating Fast Charging Infrastructure Requirements to Fully Electrify Ride-Hailing Fleets Across the United States

Ride-hailing electrification is made challenging by a variety of factors, including limited driver access to overnight charging and a nascent network of public direct-current fast charging (DCFC). This article projects the DCFC infrastructure needed to electrify ride-hailing across 384 cities in the United States. Research leveraging a novel infrastructure projection tool, Electric Vehicle Infrastructure Tool for On-Demand Mobility Services model (EVI-OnDemand), estimates that 25,400 DCFC ports capable of charging vehicles at a mean power of 150 kW are required to electrify 1.45 million ride-hailing vehicles in the baseline scenario. Results show that ride-hailing vehicles require 17.5 DCFC ports per 1000 vehicles, three times that of personal electric vehicles (EVs). Infrastructure demand is also shown to vary across cities; 63% more DCFC ports are needed to support 1000 battery EVs in Chicago versus Miami. The analysis also includes sensitivity studies that explore variation in charging demand across input assumptions, finding that charging power, vehicle class, overnight charging access rates, and port utilization influence the network size needed. Projections vary from 18,600 to 41,300 DCFC ports across sensitivity scenarios, indicating that ride-hailing electrification will require significant expansion of access to fast charging even in the most optimistic scenarios, and investments into supporting assets can reduce the scale of the public charging expansion needed.

33 ADVANCED PROPULSION SYSTEMS↗

Predicting U.S. federal fleet electric vehicle charging patterns using internal combustion engine vehicle fueling transaction statistics

Utilizing fueling transactions from internal combustion engine vehicles (ICEVs), the authors estimated how frequently midday public charging would be required for U.S. federal fleet battery electric vehicles (BEVs). Fueling transaction summary statistics are more widely available than trip-level telematics data, making this methodology more accessible and transferable to other researchers and fleet managers considering BEV replacements. For example, readers can easily apply a linear model using only the count of back-to-back fueling events at gas stations over 57 straight-line miles apart to predict days exceeding range. This linear regression predicted binned days exceeding 250 miles at 80% accuracy on a hold-out test set from the same fleet as the training data and 66 % accuracy on a new fleet displaying different driving behaviors. The authors additionally provide linear equations for days exceeding 200 and 300 miles as alternative range estimates to account for differences in BEV range and temperature impacts. Beyond the single-feature linear models which readers can apply, the authors tuned and trained other machine learning models on a variety of fueling transaction statistics including consecutive transaction distances, transaction distance from garage, estimated miles traveled from fuel economy and fuel quantity, and transaction periodicity. Utilizing a subset of 1678 light-duty federal fleet vehicles which contained daily vehicle miles traveled (VMT) in addition to fueling statistics, the authors determined which fueling transaction statistics were most relevant in predicting driving days exceeding 250 miles (an approximation of BEV rated driving range). In support of the U.S. federal fleet transition to zero-emission vehicles (ZEVs), the authors used these statistics and machine learning models to predict the frequency of BEV midday charging. After training models on the subset with VMT, the authors predicted days exceeding rated range for 112,902 light-duty vehicles operating in similar circumstances in the federal fleet using a Support Vector Regressor (SVR). In conclusion, they then used the projections as part of the ZEV Planning and Charging (ZPAC) tool to identify optimal candidates for BEVs for the federal fleet. An anonymized version of ZPAC is included in the supplementary materials.

25 ENERGY STORAGE↗

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.

Hennessy, Eleanor M. (ORCID:0000000294715765)↗

The Future of Transportation Electrification: Utility, Industry and Consumer Perspectives

Electric vehicles (EVs) today are a small part of the U.S. transportation fleet. Technological advancements, automotive industry investments and state policies are driving increased transportation electrification. Bloomberg New Energy Finance projects that by 2040, 55 percent of new sales of automobiles worldwide will be EVs. Increased transportation demand for electricity will require additional investments in the distribution system and will impact the bulk power system as load profiles change. At the same time, managed EV charging and discharging can make more efficient use of distribution system assets and increase grid flexibility. EVs also hold promise for lowering transportation costs and reducing air emissions. Infrastructure needs to electrify transportation across the United States far exceed current investment plans by EV charging companies, the public sector and others. Utilities are building “make-ready” infrastructure to ease development of public charging stations and offering rates tailored for EVs, and some utilities are directly investing in charging stations. The growth of EVs raises a number of questions for policymakers and others: How much public charging infrastructure will be needed, where should it be built and when will it be used? What role should utilities play in developing the infrastructure, compared to EV charging companies?How should charging infrastructure costs be allocated among utility customers? How should electricity rates be set to encourage efficient grid use and minimize negative grid impacts? How are states preparing for increasing electrification of the transportation sector? This report in the Future Electric Utility Regulation series from Berkeley Lab, tackles these questions and more. The report approaches the issues from three perspectives: utilities, the EV charging industry and consumers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Impacts of Biogas-to-Electricity Purchase Incentive on Electric Vehicle Market Penetration

The biogas-to-electricity pathway under the Renewable Fuel Standards allows for Renewable Identification Number (RIN) credits to be generated when electricity produced from biogas is used in the transportation sector. This study describes and evaluates a potential credit allocation method under that pathway that distributes electricity RIN (E-RIN) credits between electricity generators and plug-in electric vehicle (PEV) users and assesses the impact on EV deployment. In this study, one part of the credit value is allocated to electricity generators to offset potential higher biogas electricity generation cost, measured by the levelized cost of electricity. The other part of credit value is allocated to consumers in terms of the PEV purchase incentive to stimulate PEV sales. An iterative simulation procedure is developed to fulfill two tasks: (1) one task is to estimate the incentive amount based on various factors, such as vehicle mileage, E-RIN equivalence value, and biogas capacity, and (2) the other task is to evaluate potential impacts of the E-RIN program on electrification of the future light duty vehicle fleet and energy use. Results indicate that the E-RIN program can significantly increase PEV market share by up to 2.3 million in sales and by up to 19.7 million in fleet size in 2030. However, effectiveness of the program is subject to different factors, such as the E-RIN equivalence value, biogas electricity generation cost, biogas electricity generation capacity, and potential competition in E-RIN credits by other entities.

Xie, Fei↗