Identification of suitable sites for electric vehicle charging stations; a geographical information systems based multi criteria decision making approach

ABSTRACT

The zero emission characteristics of Electric Vehicles (EVs) play an important role in both reducing carbon emissions and creating an alternative to fossil-based fuels. Battery capacity and availability of EV charging stations are the most important criteria for EVs to become widespread. This study focuses on using location-based criteria to determine suitable locations for EV charging stations. Six criteria were determined based on academic literature and expert opinions. Euclidean distance and kernel density analysis for the criteria were determined from Geographical Information Systems (GIS), and the weights for the criteria were determined using Step-Wise Weight Assessment Ratio Analysis (SWARA). C₂ was found to be the most significant criterion with a weight of 0.316 and C₅ the least important with a weight of 0.088. The six criteria maps were combined as a weighted map and 21 potential locations within the range of 0–0.175 pixel values were identified in the study area. The locations were ranked using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to determine the most suitable sites. According to the pixel values of the criteria maps, CS5 determined as the most suitable site, followed by CS2 and CS4. This study presents a new perspective for the selection of suitable sites for EV charging stations, using a GIS based SWARA and TOPSIS methods.

KEYWORDS:

• Electric vehicle
• site selection
• charging station
• SWARA
• GIS
• TOPSIS

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Notes on contributors

Aziz Sisman

Dr. Aziz ŞİŞMAN is working as a Professor at Ondokuz Mayıs University, Faculty of Engineering Department of Geomatics Engineering in Samsun, Türkiye. He has done Master Degree Geomatics Engineering Program at Karadeniz Technical University and PhD in Remote Sensing and GIS Program at Yıldız Technical University. His current research interest includes GIS, Land Management, Multi Criteria Decision Making.