DOI: 10.5281/zenodo.13306893
title: Transportation Electrification Load Profiles by Balancing Authority and State-Level Electrification Rates in the Western United States for GODEEEP

description: Time-series hourly electric charging load profiles for the transportation sector across Balancing Authorities (BAs) in the Western Electricity Coordinating Council (WECC) interconnect, annual fleet sizes by state and vehicle type, annual transportation sector energy usage by state and fuel, and annual transportation fuel usage by state. The data is provided for three different socioeconomic pathways and two different climate pathways, resulting in four total scenarios. The socioeconomic pathways--Net-Zero (nz_climate), Net-Zero allowing for Carbon Capture Sequestration (CCS) technology (nz_ccs_climate), and Net-Zero allowing for CCS with Inflation Reduction Act (IRA) policies (nz_ira_ccs_climate)--are described by https://doi.org/10.5281/zenodo.10642507. The climate pathways--Representative Concentration Pathway (RCP) 4.5 cooler (rcp45cooler) and RCP 8.5 hotter (rcp85hotter)--are described by https://doi.org/10.57931/1885756. The climate influence is only considered for Light Duty Vehicles (LDVs).

For additional details please consult the paper Acharya et al 2024, Impact of the Inflation Reduction Act and Carbon Capture on Transportation Electrification for a Net-Zero Western U.S. Grid, submitted, and the code repository https://github.com/GODEEEP/transportation_electrification.

A brief summary of the files and directories in this data package is provided below. Text within chevrons implies a multiplicity of files, one for each actual value.



nz_climate



rcp45cooler



<balancing authority>_hourly_transportation_load_<socioeconomic pathway>_<climate scenario>_<year>.csv



rcp85hotter



<balancing authority>_hourly_transportation_load_<socioeconomic pathway>_<climate scenario>_<year>.csv





nz_ccs_climate



rcp45cooler



<balancing authority>_hourly_transportation_load_<socioeconomic pathway>_<climate scenario>_<year>.csv



rcp85hotter



<balancing authority>_hourly_transportation_load_<socioeconomic pathway>_<climate scenario>_<year>.csv





nz_ira_ccs_climate



rcp45cooler



<balancing authority>_hourly_transportation_load_<socioeconomic pathway>_<climate scenario>_<year>.csv



rcp85hotter



<balancing authority>_hourly_transportation_load_<socioeconomic pathway>_<climate scenario>_<year>.csv





WECC_hourly_transportation_load_<socioeconomic pathway>_<climate scenario>_<year>.csv

EV_electric_and_total_energy.csv

LDV_fleet_size_all_fuel_types_state_wise.csv

MDV_fleet_size_all_fuel_types_state_wise.csv

HDV_fleet_size_all_fuel_types_state_wise.csv


 

Hourly transportation load:



time - ISO 8601 timestamp representing the end of the hourly timestep; values are reported as the summation over the preceding hour

balancing_authority - Acronym of the balancing authority for this data point

LDV_load_MWh - Energy consumed by the charging of Light Duty Vehicles (LDVs) during the previous hour in Megawatt hours

MDV_load_MWh - Energy consumed by the charging of Medium Duty Vehicles (MDVs) during the previous hour in Megawatt hours

HDV_load_MWh - Energy consumed by the charging of Heavy Duty Vehicles (HDVs) during the previous hour in Megawatt hours

passenger_rail_load_MWh - Energy consumed by the charging of passenger rail vehicles during the previous hour in Megawatt hours

freight_rail_load_MWh - Energy consumed by the charging of freight rail vehicles during the previous hour in Megawatt hours

aviation_load_MWh - Energy consumed by the charging of aviation vehicles during the previous hour in Megawatt hours

ship_load_MWh - Energy consumed by the charging of ships during the previous hour in Megawatt hours

transportation_load_MWh - Total energy consumed by the charging of vehicles during the previous hour in Megawatt hours (summation of the other columns)


The WECC files provide summations of all BAs for each scenario, with the same columns as above excepting balancing_authority

State-wise fleet sizes by vehicle type:



scenario - the socioeconomic pathway, one of nz_climate, nz_ccs_climate, or nz_ira_ccs_climate

state - two letter abbreviation of the state within the Western U.S. Interconnection

year - 5 year increments from 2020 to 2050

technology - fuel type such as BEV (battery electric vehicle), FCEV (fuel cell electric vehicle), hybrid liquids and liquids (refined liquids)

veh_type - one of LDV, MDV, or HDV (Light, Medium, or Heavy Duty Vehicle)

fleet_size - the number of vehicles


To calculate an electrification rate in terms of fleet size for a given scenario, state, year, and vehtype, we divide the fleetsize for BEV technology by the summation of fleet_size for all technologies.

State-wise electric and total energy for LDVs, MDVs, and HDVs:



state - two letter abbreviation of the state within the Western U.S. Interconnection

year - 5 year increments from 2020 to 2050

scenario - the socioeconomic pathway, one of nz_climate, nz_ccs_climate, or nz_ira_ccs_climate

hdv_total - energy in ExaJoules consumed by all HDVs irrespective of fuel type

ldv_total - energy in ExaJoules consumed by all LDVs irrespective of fuel type

mdv_total - energy in ExaJoules consumed by all MDVs irrespective of fuel type

hdv_electric - electric energy in ExaJoules consumed by HDVs

ldv_electric - electric energy in ExaJoules consumed by LDVs

mdv_electric - electric energy in ExaJoules consumed by MDVs


To calculate the electrification rate in terms of EV energy for a given scenario, state, year, and veh_type, we divide electric energy by the total energy.

State-wise transportation fuel mix:



state - two letter abbreviation of the state within the Western U.S. Interconnection

year - 5 year increments from 2020 to 2050

scenario - the socioeconomic pathway, one of nz_climate, nz_ccs_climate, or nz_ira_ccs_climate

hydrogen - hydrogen energy in ExaJoules consumed by the transportation sector

electricity - electric energy in ExaJoules consumed by the transportation sector

refined liquids - refined liquid energy in ExaJoules consumed by the transportation sector




Changelog:



v2.0.0 - new set of scenarios; fuel mix data added


 

This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL).

PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.