Published September 2016 | Version v1
Journal article

Assessing the impact of policy interventions on the adoption of plug-in electric vehicles: An agent-based model

  • 1. Brigham Young University, Marriottt School of Management, 764 TNRB, Provo, UT 84602 (United States)
  • 2. University of Kansas, School of Public Affairs and Administration, Wescoe Hall, Room 4060P, Lawrence, KS 66045 (United States)

Description

Heightened concern regarding climate change and energy independence has increased interest in plug-in electric vehicles as one means to address these challenges and governments at all levels have considered policy interventions to encourage their adoption. This paper develops an agent-based model that simulates the introduction of four policy scenarios aimed at promoting electric vehicle adoption in an urban community and compares them against a baseline. These scenarios include reducing vehicle purchase price via subsidies, expanding the local public charging network, increasing the number and visibility of fully battery electric vehicles (BEVs) on the roadway through government fleet purchases, and a hybrid mix of these three approaches. The results point to the effectiveness of policy options that increased awareness of BEV technology. Specifically, the hybrid policy alternative was the most successful in encouraging BEV adoption. This policy increases the visibility and familiarity of BEV technology in the community and may help counter the idea that BEVs are not a viable alternative to gasoline-powered vehicles. - Highlights: •Various policy interventions to encourage electric vehicle adoption are examined. •An agent based model is used to simulate individual adoption decisions. •Policies that increase the familiarity of electric vehicles are most effective.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enpol.2016.05.039

Additional details

Identifiers

DOI
10.1016/j.enpol.2016.05.039;
PII
S0301-4215(16)30269-5;

Publishing Information

Journal Title
Energy Policy
Journal Volume
96
Journal Page Range
p. 105-118
ISSN
0301-4215
CODEN
ENPYAC

Optional Information

Copyright
Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.