Selection of electric vehicle charging station locations with multi criteria decision making techniques : Case study in Ankara

Global warming and climate crisis are one of the major problems, affecting humankind in recent years. Replacing fossil fuels with renewable energy sources; play an important role in solving environmental problems that grow day by day, especially global warming, climate change and carbon emissions. In order to take the necessary precautions, one of the responsible industries, the automotive industry has turned its face to electric vehicles as environmentally friendly solutions that rely on renewable energy sources.. Nowadays, the concerns of users towards electrical vehicles have to be resolved in order to fasten the adaptation process to this new technology. With this perspective, especially to resolve the concerns that users have about the range and usage concepts of these vehicles, it is necessary to create sufficient charging station infrastructure that complies with users demand and usage scenarios. In this study, the potentials of selected charging station locations in Middle East Technical University Campus, in Ankara, capital city of Turkey, are classified by using data, criteria, and expert opinions in various Multi-Criteria Decision Making Techniques. Analytical hierarchy process (AHP) integrated technique for order preference by similarity to ideal solution (TOPSIS) and AHP integrated Vlsekriterijumska Optimizacijia I Kompromisno Resenje (VIKOR) methods are utilized together to select the best locations in the campus. Initially 4 compherensive criteria and 10 sub-criteria are determined from different aspects. Experts' ratings are used with Analytical hierarchy process (AHP) method for determination of 10 criteria weights. Potentials of selected locations are investigated and ranked by using VIKOR and TOPSIS methods. Both techniques indicate that A6 is the optimal location for charging station deployment. In the proposed methodology robustness and effectiveness of the study is demonstrated by sensitivity analysis. This study aims to establish a scientific tool for respective authorities and decision makers.