Mujde Erol Genevois, Hatice Kocaman



Locating Electric Vehicle Charging Stations in Istanbul with AHP Based Mathematical Modelling

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In recent years, because of the soaring prices of oil and the environmental issues, automakers have offered electric vehicles for sustainable transportation. However, the transition to EVs is currently facing various shortcomings among which are: the high cost of EV batteries and their limited driving range, and underdeveloped charging station infrastructure. To overcome these shortcomings, it is significant to install sufficient charging station to the critical sites. In this paper, we address the problem of where to locate charging stations in districts of Istanbul, Turkey. The problem of where to locate electric vehicle charging station can be grouped as a decision making problem while many criteria and alternatives have to be considered simultaneously. Therefore, ten alternative locations are identified in Kadikoy and Atasehir, two districts of Istanbul. Three main criteria are formed from the literature review to compare these alternative locations with each other. Analytic Hierarchy Process (AHP) methodology is used to obtain composite weight of each alternative locations and to rank them. Then these weights are used as input for mathematical model to determine the number of charging station to install. The mathematical model is formulated to maximize the user utility under budget and capacity constraints to obtain optimal number of charging station for each alternative point. Therefore, the composite weights used in mathematical model affect the number of charging stations to locate. Finally, the integrating methodology yields effective and robust results.


Electric vehicle charging station, AHP, Mathematical modelling, Location selection


[1] Afroditi, M. Boile, S. Theofanis, E. Sdoukopoulos and D. Margaritis, Electric Vehicle Routing Problem with industry constraints: trends and insights for future research, Transportation Research Procedia, Vol.3, 2014, pp. 452 – 459.

[2] W. Feng and M. A. Figliozzi, Conventional vs electric commercial vehicle fleets: A case study of economic and technological factors affecting the competitiveness of electric commercial vehicles in the USA, Procedia - Social and Behavioral Sciences, Vol. 39, 2012, pp. 702- 711.

[3] H. Gavranović, A. Barut, G. Ertek, O. B. Yüzbaşıoğlu, O. Pekpostalcı and Ö. Tombuş, Optimizing the electric charge station network of EŞARJ, Procedia Computer Science, Vol. 31, 2014, pp. 15 – 21.

[4] Wang, Y.-W., An optimal location choice model for recreation-oriented scooter recharge stations, Transportation Research, Vol. 12, 2007, pp. 231–237.

[5] Meng, W., & Kai, L., Optimization of Electric Vehicle Charging Station Location Based on Game Theory, Transportation, Mechanical and Electrical Engineering, 2011, pp. 809-812.

[6] Jia, L., Hu, Z., Song, Y., & Luo, Z., Optimal Siting and Sizing of Electric Vehicle Charging Stations, Electric Vehicle Conference, 2012, pp. 1-6.

[7] Chen, T., Kockelman, K., & Khan, M., The electric vehicle charging station location problem: a parking-based assignment method for Seattle, Transportation Research Board 92nd Annual Meeting, Vol. 340, 2013, pp. 13-1254. Washington DC.

[8] Shi, R., & Lee, K. Multi-objective Optimization of Electric Vehicle Fast Charging Stations with SPEA-II, IFAC-PApersOnLine, Vol.48, No.30, 2015, pp. 535-540.

[9] Shahkari, N., Cai, H., Turkay, M., & Xu, M., Optimal Locations of electric public charging stations using real world vehicle travel patterns. Transportation Research Part D: Transport and Environment, Vol.41, 2015, pp. 165-176.

[10] He, F., Yin, Y., & Zhou, J., Deploying Public Stations for Electric Vehicles on Urban Road Networks, Transportation Part C: Emerging Technologies, Vol.60, 2015, pp. 227-240.

[11] Nakamura, T., Schmöcker, J.-D., Fujii, A., Sun, W., & Uno, N., Location Optimization of Charging Stations for Electric Fleet Truck Based on Given Tour PatternsTERNS, No.17-05711, 2017.

[12] Zhou, S., Liu, W., & Chang, W., An improved TOPSIS with weighted hesitant vague information, Chaos, Solitons & Fractals, Vol. 89, 2016, pp. 47-53.

[13] Wu, Y., Yang, M., Zhang, H., Chen, K., & Wang, Y., Optimal site selection of electric vehicle charging stations based on a cloud model and the PROMETHEE method, Energies, Vol.9, No.3, 2016, pp. 1-20.

[14] Li, S., Huang, Y., & Mason, S. J., A multi-period Optimization Model for the Deployment of the Public Electrric Vehicle Charging Stations on Network, Transportation Research Part C: Emerging Technologies, Vol.65, 2016, pp. 128-143.

[15] Alegre, S., Míguez, J., & Carpio, J., Modelling of electric and parallel-hybrid electric vehicle using Matlab/Simulink environment and planning of charging stations through a geographic information system and genetic algorithms, Renewable and Sustainable Energy Reviews, Vol.74, 2017, pp. 1020-1027.

[16] Awasthi, A., Venkitusamy, K., Padmanaman, S., Selvamuthukumaran, R., Blaabjerg, F., & Singh, A., Optimal Planning of electric vehicle charging stations at the distribution system using hybrid optimization algorithm, Energy, Vol. 133, 2017, pp. 70-78.

[17] Yang, J., Dong, J., & Hu, L. (2017). A data-driven Optimization-based Approach for Sitting and sizing of Electric Taxi Charging Stations. Transportation Research Part C: Emerging Technologies, Vol.77, 2017, pp. 462-477.

[18] Wu, F., & Sioshansi, R., A Stochastic flow-capturing model to optimize the location of fast-charging stations with uncertain electric vehicle flows. Transportation Research Part D: Transport and Environment, Vol.53, 2017, pp 354-376.

[19] R. Abu Taha, Multi-criteria Applications in Renewable Energy Analysis: A Literature Review, Portland, OR, IEEE, 2011, pp. 1-8.

[20] A. Ishizaka, and P. Nemery, Multi-Criteria Decision Analysis: Methods and Software. John Wiley & Sons, 2012.

[21] D. Efthymiou, C. Antoniou, Y. Tyrinopoylos, and E. Mitsakis, Spatial exploration of Effective electric vehicle infrastructure location, Procedia-Social and Behavioral Sciences, Vol.48, 2012, pp. 765-774.

[22] S. Guo and H. Zhao, Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective, Applied Energy, Vol. 158, 2015, pp. 390-402.

[23] Y. Liu, B. Zhou, C. Feng, and S. Pu, Application of comprehensive evaluation method integrated by Delphi and GAHP in optimal siting of electric vehicle charging station, International Conference on Control Engineering and Communication Technology, 2012, pp. 88-91.

[24] K. Xu, P. Yi and Y. Kandukuri, Location Selection of Charging Station for Battery Electric Vehicles in an Urban Area. International Journal of Engineering Research and Science & Technology, Vol.2, No.3, 2013, pp. 15-23.

[25] M. Jin, R. Shi, N. Zhang, and Y. Li, Study on Multi-Level Layout Planning of Electric Vehicle Charging Stations Based on an Improved Genetic Algorithm, International Journal of Smart Grid and Clean Energy, Vol.2, No.2, 2012, pp. 277-282.

[26] Tang, Z., Guo, C., Hou, P., &Fan, Y., Optimal Sitting of Elecric Vehicle Charging Stations Based on Voronio Diagram and FAHP Method. Enery and Power Engineering, Vol.5, No.04, 2013, pp. 1404–1409.

[27] Yağcıtekin, B., Uzunuğlu, M., & Karakaş, A., A new deployment method for electric vehicle charging infrastructure. Turkish Journal of Electrical Engineering & Computer Sciences, Vol.24, No.3, 2016, pp. 1292-1305.

Cite this paper

Mujde Erol Genevois, Hatice Kocaman. (2018) Locating Electric Vehicle Charging Stations in Istanbul with AHP Based Mathematical Modelling. International Journal of Transportation Systems, 3, 1-10


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