Work

Behavioral and infrastructure influences on electric vehicle charging and grid impact

Year: 2025

Type: article

Abstract: Electric vehicle (EV) adoption reshapes travel and electricity demand. We integrate a Cumulative Prospect Theory (CPT) model with a dynamic reference-point mechanism into daily travel routines derived from the 2022 U.S. National Household Travel Survey. Using empirical data from 283 EV users, the simulation generates charging behavior for 10,000 synthetic individuals. Four behavioral archetypes emerge: Home-Focused, Work-Focused, Anxious Opportunistic, and Long-Distance drivers, with unique charging preferences and infrastructure requirements. While behavioral factors significantly influence individual charging decisions, our sensitivity analysis demonstrates that varying CPT parameters across their observed ranges alters aggregate daily energy consumption by less than 1%. Conversely, infrastructure changes, such as increased workplace charging, significantly shift evening charging to morning (up to 50.9%) and reduce evening peak load (9.3% reduction). These results suggest that while behavioral modeling is important at the individual level, infrastructure design plays a more critical role in managing overall grid impacts.

Source: Transportation Research Part D Transport and Environment

DOI: 10.1016/j.trd.2025.105011

Authors: Yuxi Shen, Alyssa Ryan, Melrose Pan, Xiaoqin Fu, Liang Zhang

Institutions: University of Arizona, Oak Ridge National Laboratory

Language: English

Topic: Electric Vehicles and Infrastructure

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $3,450