Abstract
This paper examines the possibility of locating electric vehicle charging stations using multi-criteria decision analysis (MCDA) and GIS. The study presents an integrated approach, which can be helpful in spatial planning. Recent years have witnessed a growing interest in using alternative power sources for motor vehicles. It is stimulated by top-down factors, such as regulations introduced by the European Commission or the introduction of the so-called “clean transport zones” by some local governments, as well as the bottom-up ones, including the increase in the cost of maintaining fossil fuel-powered cars. Local governments can employ the analysis presented in the paper to find a coherent development strategy for using electric vehicles (EVs) in cities. Based on the verified hypothesis, the Łódź city area has diverse suitability for EV charging stations, with predominant unfavourable regions for such investments. The research aims to find the methodology for performing the suitability analysis to locate new infrastructure elements in an urban space.
References
Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649-655. https://doi.org/10.1016/0377-2217(95)00300-2
Csutora, R., & Buckley, J. J. (2001). Fuzzy hierarchical analysis: The Lambda-Max method. Fuzzy Sets and Systems, 120(2), 181-195. https://doi.org/10.1016/s0165-0114(99)00155-4
Dashora, Y., Barnes, J. W., Pillai, R. S., Combs, T. E., Hilliard, M., & Chinthavali, M. S. (2010). The PHEV charging infrastructure planning (PCIP) problem. International Journal of Emerging Electric Power Systems, 11(2). https://doi.org/10.2202/1553-779X.2482
Guler, D., & Yomralioglu, T. (2020). Suitable location selection for the electric vehicle fast charging station with AHP and fuzzy AHP methods using GIS. Annals of GIS, 26(2), 169-189. https://doi.org/10.1080/19475683.2020.1737226
Guo, S., & Zhao, H. (2015). Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective. Applied Energy, 158, 390-402. https://doi.org/10.1016/j.apenergy.2015.08.082
Jarek, S. (2016). Removing Inconsistency in Pairwise Comparisons Matrix in the AHP. Multiple Criteria Decision Making, 11, 63-76. https://doi.org/10.22367/mcdm.2016.11.05
Krejčí, J., Pavlačka, O., & Talašová, J. (2017). A fuzzy extension of Analytic Hierarchy Process based on the constrained fuzzy arithmetic. Fuzzy Optimization and Decision Making, 16(1), 89-110. https://doi.org/10.1007/s10700-016-9241-0
Kutlu, A. C., & Ekmekçioǧlu, M. (2012). Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP. Expert Systems with Applications, 39(1), 61-67. https://doi.org/10.1016/j.eswa.2011.06.044
Liu, F., Peng, Y., Zhang, W., & Pedrycz, W. (2017). On Consistency in AHP and Fuzzy AHP. Journal of Systems Science and Information, 5(2), 128-147. https://doi.org/doi:10.21078/JSSI-2017-128-20
Mikhailov, L. (2003). Deriving priorities from fuzzy pairwise comparison judgements. Fuzzy Sets and Systems, 134(3), 365-385. https://doi.org/10.1016/S0165-0114(02)00383-4
Pietrzak, K., & Pietrzak, O. (2020). Environmental effects of electromobility in a sustainable urban public transport. Sustainability, 12(3), 1052. https://doi.org/10.3390/su12031052
Pietrzak, O., & Pietrzak, K. (2021). The economic effects of electromobility in sustainable urban public transport. Energies, 14(4), 878. https://doi.org/10.3390/en14040878
Polskie Stowarzyszenie Paliw Alternatywnych. (2022a). Co 7. samochód sprzedawany w Polsce w 2025 r. może być elektryczny. https://pspa.com.pl/2022/raport/co-7-samochod-sprzedawany-w-polsce-w-2025-r-moze-byc-elektryczny/
Polskie Stowarzyszenie Paliw Alternatywnych. (2022b). Licznik Elektromobilności: znaczny wzrost liczby rejestracji samochodów elektrycznych po trzech kwartałach 2022 r. https://pspa.com.pl/2022/informacja/licznik-elektromobilnosci-znaczny-wzrost-liczby-rejestracji-samochodow-elektrycznych-po-trzech-kwartalach-2022-r/
Polskie Stowarzyszenie Paliw Alternatywnych. (2022c). Pojazdy elektryczne zdominują 70% rynku już w 2040 r. [RAPORT]. https://pspa.com.pl/2022/raport/pojazdy-elektryczne-zdominuja-70-rynku-juz-w-2040-r-raport/
Quak, H., Nesterova, N., Van Rooijen, T., & Dong, Y. (2016). Zero Emission City Logistics: Current Practices in Freight Electromobility and Feasibility in the Near Future. Transportation Research Procedia, 14, 1506-1515. https://doi.org/10.1016/j.trpro.2016.05.115
Rokicki, T., Bórawski, P., Bełdycka-Bórawska, A., Żak, A., & Koszela, G. (2022). Development of electromobility in European Union countries under COVID-19 conditions. Energies, 15(1), 1-24. https://doi.org/10.3390/en15010009
Szymańska, P., & Szczur, A. (2019). Kryteria oceny lokalizacji punktów ładowania samochodów elektrycznych. Studium przypadku: sieć punktów ładowania w Poznaniu. Prace Komisji Geografii Komunikacji PTG, 22(2), 20-33. https://doi.org/10.4467/2543859xpkg.19.008.11148
Trzaskalik, T. (2014). Wielokryterialne wspomaganie decyzji. Metody i zastosowania. Warszawa: PWE.
Wu, Y., Yang, M., Zhang, H., Chen, K., & Wang, Y. (2016). Optimal site selection of electric vehicle charging stations based on a cloud model and the PROMETHEE method. Energies, 9(3), 1-20. https://doi.org/10.3390/en9030157
Zhao, H., & Li, N. (2016). Optimal siting of charging stations for electric vehicles based on fuzzy Delphi and hybrid multi-criteria decision making approaches from an extended sustainability perspective. Energies, 9(4), 1-22. https://doi.org/10.3390/en9040270
Zhu, Z. H., Gao, Z. Y., Zheng, J. F., & Du, H. M. (2016). Charging station location problem of plug-in electric vehicles. Journal of Transport Geography, 52, 11-22. https://doi.org/10.1016/j.jtrangeo.2016.02.002
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Copyright (c) 2023 Economics and Environment