TEMPO: Transportation Energy & Mobility Pathway Options Model

Abstract

The electric vehicle charging dataset—produced using the Transportation Energy & Mobility Pathway Options (TEMPO) model—projects spatially, demographically, and temporally resolved passenger electric vehicle charging demand. The data are hourly annual for 2024-2050 based on 2012 actual meteorological year (AMY) weather; are available for three scenarios of light-duty passenger electric vehicle adoption, 3,108 counties in the contiguous United States (CONUS), 720 household and vehicle types, and two charging types (L1&L2 and DCFC); and were produced by running the TEMPO model at the county-level. The three adoption scenarios are:

AEO Reference Case, which is aligned with the U.S. EIA Annual Energy Outlook 2018 EFS High Electrification, which is aligned with the High Electrification scenario of the Electrification Futures Study 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: Drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress. Immediate charging: 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 vehicle state of charge is maximized at all times. This bounding case would minimize range anxiety, but is based on unrealistically high electric vehicle service equipment (EVSE) (i.e., charger) access, and unrealistic plug-in behavior. (Regarding the latter point, battery electric vehicles [BEVs] are often only plugged in a few times per week, but ubiquitous-immediate charging can result in dozens of charging sessions per week.)