This data set includes modeling results from “The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure” including region-specific [i.e., national, state, and core-based statistical area (CBSA)—cities/towns] electric vehicle supply equipment (EVSE) port count requirements in 2025 and 2030 for multiple scenarios described in the study. Please cite as: Wood, E., B. Borlaug, M. Moniot, D.-Y. Lee, Y. Ge, F. Yang, and Z. Liu. 2023. The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5400-85654.

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

Federal, state, and municipal electric vehicle fleet hourly load datasets at the Uber H3 hex, county, and city resolutions, as described in Singer et al. (2025).Please cite as:Singer, Mark, Cabell Hodge, Kara Podkaminer, and Brennan Borlaug. 2025. Initial Estimate of Electricity Demand for Federal, State, and Municipal Electric Vehicle Fleets in the United States. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5400-92142. https://www.nrel.gov/docs/fy25osti/92142.pdf (forthcoming)

This file includes light-duty vehicle (LDV) stock, sales, and energy and emissions data for the scenarios reported in "Electrification Pathways for U.S. Passenger Vehicles." Data is reported annually at the national level for the United States for each of the six scenarios described in the accompanying paper.

딥러닝 모델을 이용하여 전국 시도별 전기자동차 전력수요량을 예측한 모델.예측 범위의 25%, 50%, 75% 전력수요량 제공. 시도별 전기자동차 충전소 입지 선정에 활용 가능.

This data set includes the 24-hour fleet depot charging load profiles (15-min. average demand) and substation load integration assessment results produced for the study, "Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems", published in 2021 (https://doi.org/10.1038/s41560-021-00855-0). The code developed to generate these load profiles is publicly available at https://github.com/NREL/hdev-depot-charging-2021. Please cite as: Borlaug, B., Muratori, M., Gilleran, M. et al. Heavy-duty truck electrification and the impacts of depot charging on electricity distribution systems. Nat Energy 6, 673–682 (2021). https://doi.org/10.1038/s41560-021-00855-0

This data set includes the 24-hour fleet depot charging load profiles (15-min. average demand) and substation load integration assessment results produced for the study, "Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems", published in 2021 (https://doi.org/10.1038/s41560-021-00855-0). The code developed to generate these load profiles is publicly available at https://github.com/NREL/hdev-depot-charging-2021. Please cite as: Borlaug, B., Muratori, M., Gilleran, M. et al. Heavy-duty truck electrification and the impacts of depot charging on electricity distribution systems. Nat Energy 6, 673–682 (2021). https://doi.org/10.1038/s41560-021-00855-0