Spatiotemporal model for estimating electric vehicles adopters

The use of fossil fuel vehicles is one of the factors responsible for the degradation of air quality in urban areas. In order to reduce levels of air pollution in metropolitan areas, several countries have encouraged the use of electric vehicles in the cities. However, due to the high investment cos...

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Veröffentlicht in:Energy (Oxford) 2019-09, Vol.183, p.788-802
Hauptverfasser: Rodrigues, João L., Bolognesi, Hugo M., Melo, Joel D., Heymann, Fabian, Soares, F.J.
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container_end_page 802
container_issue
container_start_page 788
container_title Energy (Oxford)
container_volume 183
creator Rodrigues, João L.
Bolognesi, Hugo M.
Melo, Joel D.
Heymann, Fabian
Soares, F.J.
description The use of fossil fuel vehicles is one of the factors responsible for the degradation of air quality in urban areas. In order to reduce levels of air pollution in metropolitan areas, several countries have encouraged the use of electric vehicles in the cities. However, due to the high investment costs in this class of vehicles, it is expected that the spatial distribution of electric vehicles' adopters will be heterogeneous. The additional charging power required by electric vehicles' batteries can change operation and expansion planning of power distribution utilities. In addition, urban planning agencies should analyze the most suitable locations for the construction of electric vehicle recharging stations. Thus, in order to provide information for the planning of electric mobility services in the city, this paper presents a spatiotemporal model for estimating the rate of electric vehicles' adopters per subareas. Results are spatial databases that can be viewed in geographic information systems to observe regions with greater expectancy of residential electric vehicle adopters. These outcomes can help utilities to develop new services that ground on the rising availability of electric mobility in urban zones. •The proposed methodology estimates the rate of EVs' adopters per subareas.•The urban spatial interaction for the possibility of purchasing EVs are characterized.•The spatial distribution of the purchase of EVs in the first years of their penetration is estimated.•The result of the proposal can be processed by any agency's GIS involved.
doi_str_mv 10.1016/j.energy.2019.06.117
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source ScienceDirect Journals (5 years ago - present)
subjects Air pollution
Air quality
Batteries
Electric power distribution
Electric utilities
Electric vehicle adopters
Electric vehicles
Estimation
Expectancy
Fossil fuels
Geographic information systems
Geographical information systems
Metropolitan areas
Mobility
Outdoor air quality
Pollution control
Pollution levels
Remote sensing
Spatial distribution
Spatial regression
Sustainable city planning
Urban areas
Urban planning
title Spatiotemporal model for estimating electric vehicles adopters
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