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A location model for electric vehicle (EV) public charging stations based on drivers' existing activities.

Authors :
Pan, Long
Yao, Enjian
Yang, Yang
Zhang, Rui
Source :
Sustainable Cities & Society; Aug2020, Vol. 59, pN.PAG-N.PAG, 1p
Publication Year :
2020

Abstract

• A location model is established based on existing activity patterns and time budgets. • The location model can minimize the trip loss of predetermined budget. • The vast majority of EV drivers' travel demand can be fulfilled. • Some drivers have to change activity patterns even in a larger charging network. • Missed-trip drivers are usually with longer travel distances and without home chargers. Deploying electric vehicle (EV) public charging stations could alleviate range anxiety of EV drivers, ensuring EVs to provide similar performances as internal combustion engine vehicles by maintaining their existing activities. This study develops a location model for EV public charging stations aiming to maximumly maintain the existing activities of EV drivers. First, a deterministic process of EV charging choice is proposed to simulate EV drivers' charging choice behavior. This process involves EV drivers' existing activities, home and public charging availability, range anxiety, and the energy consumption of remaining trips. Second, a coverage location model for EV public charging stations is proposed, aiming to maximize EV drivers' existing activities. Finally, the proposed model is applied to Beijing, China as a case study. The preliminary characteristics of drivers' trips are obtained, showing that the necessary energy for 46 % drivers on five weekdays exceeds the capacity of EV battery. The optimal solutions show that a decent amount of charging network could fulfill 90 % EV drivers' travel demand without changing their daily trips. The planned public charging stations mainly cover the high-tech and financial areas. The missed-trip EV drivers are also analyzed, being characterized with longer travel distances and without owning home chargers. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22106707
Volume :
59
Database :
Supplemental Index
Journal :
Sustainable Cities & Society
Publication Type :
Academic Journal
Accession number :
143417160
Full Text :
https://doi.org/10.1016/j.scs.2020.102192