Electric Charging Demand Location Model—A User- and Destination-Based Locating Approach for Electric Vehicle Charging Stations
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Institute for Applied Informatics, Deggendorf Institute of Technology, Grafenauer Straße 22, 94078 Freyung, Germany
2
Interfaculty Department of Geoinformatics Z_GIS, University of Salzburg, Schillerstraße 50, 5020 Salzburg, Austria
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(8), 2301; https://doi.org/10.3390/su11082301
Received: 21 February 2019 / Revised: 11 April 2019 / Accepted: 11 April 2019 / Published: 17 April 2019
(This article belongs to the Special Issue Sustainable Transport: Transport, Environment, and Development)
In recent years, with the increased focus on climate protection, electric vehicles (EVs) have become a relevant alternative to conventional motorized vehicles. Even though the market share of EVs is still comparatively low, there are ongoing considerations for integrating EVs in transportation systems. Along with pushing EV sales numbers, the installation of charging infrastructure is necessary. This paper presents a user- and destination-based approach for locating charging stations (CSs) for EVs—the electric charging demand location (ECDL) model. With regard to the daily activities of potential EV users, potential positions for CSs are derived on a micro-location level in public and semipublic spaces using geographic information systems (GIS). Depending on the vehicle users’ dwell times and visiting frequencies at potential points of interest (POIs), the charging demand at such locations is calculated. The model is mainly based on a survey analyzing the average time spent per daily activity, regional data about driver and vehicle ownership numbers, and the georeferenced localization of regularly visited POIs. Optimal sites for parking and charging EVs within the POIs neighborhood are selected based on walking distance calculations, including spatial neighborhood effects, such as the density of POIs. In a case study in southeastern Germany, the model identifies concrete places with the highest overall demand for CSs, resulting in an extensive coverage of the electric energy demand while considering as many destinations within the acceptable walking distance threshold as possible.
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Keywords:
electric vehicle; charging station; spatial localization; GIS; user- and destination-based; point of interest
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MDPI and ACS Style
Pagany, R.; Marquardt, A.; Zink, R. Electric Charging Demand Location Model—A User- and Destination-Based Locating Approach for Electric Vehicle Charging Stations. Sustainability 2019, 11, 2301. https://doi.org/10.3390/su11082301
AMA Style
Pagany R, Marquardt A, Zink R. Electric Charging Demand Location Model—A User- and Destination-Based Locating Approach for Electric Vehicle Charging Stations. Sustainability. 2019; 11(8):2301. https://doi.org/10.3390/su11082301
Chicago/Turabian StylePagany, Raphaela, Anna Marquardt, and Roland Zink. 2019. "Electric Charging Demand Location Model—A User- and Destination-Based Locating Approach for Electric Vehicle Charging Stations" Sustainability 11, no. 8: 2301. https://doi.org/10.3390/su11082301
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