Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022
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.
Citation Formats
National Renewable Energy Laboratory. (2023). Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022 [data set]. Retrieved from https://dx.doi.org/10.25984/2373091.
Yip, Arthur, Hoehne, Christopher, Jadun, Paige, Ledna, Catherine, Hale, Elaine, Muratori, Matteo, Thom, Daniel, Mooney, Meghan, and Liu, Lixi. Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022. United States: N.p., 29 Aug, 2023. Web. doi: 10.25984/2373091.
Yip, Arthur, Hoehne, Christopher, Jadun, Paige, Ledna, Catherine, Hale, Elaine, Muratori, Matteo, Thom, Daniel, Mooney, Meghan, & Liu, Lixi. Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022. United States. https://dx.doi.org/10.25984/2373091
Yip, Arthur, Hoehne, Christopher, Jadun, Paige, Ledna, Catherine, Hale, Elaine, Muratori, Matteo, Thom, Daniel, Mooney, Meghan, and Liu, Lixi. 2023. "Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022". United States. https://dx.doi.org/10.25984/2373091. https://data.openei.org/submissions/5958.
@div{oedi_5958, title = {Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022}, author = {Yip, Arthur, Hoehne, Christopher, Jadun, Paige, Ledna, Catherine, Hale, Elaine, Muratori, Matteo, Thom, Daniel, Mooney, Meghan, and Liu, Lixi.}, abstractNote = {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. }, doi = {10.25984/2373091}, url = {https://data.openei.org/submissions/5958}, journal = {}, number = , volume = , place = {United States}, year = {2023}, month = {08}}
https://dx.doi.org/10.25984/2373091
Details
Data from Aug 29, 2023
Last updated Jun 17, 2024
Submitted Jun 12, 2024
Organization
National Renewable Energy Laboratory
Contact
Elaine T. Hale
303.384.7812
Authors
Research Areas
Keywords
energy, power, TEMPO, dsgrid, demand-side grid, demand model, transportation, electric vehicle, EV, electrification, bulk power systems, energy modeling, projection, long-term load forecasting, electric vehicle charging, passenger vehicles, model, charging load, United States, computational scienceDOE Project Details
Project Name Demand-side Grid (dsgrid)
Project Number 29323