Suitable law-based location selection of high-power electric vehicles charging stations on the TEN-T core network for sustainability: a case of Poland

Maciej Mazur; Jacek Dybała; Aldona Kluczek

doi:10.61089/aot2024.1mrj1x75

Authors

Maciej Mazur Polish Alternative Fuels Association Author https://orcid.org/0009-0003-1370-6758
Jacek Dybała Warsaw University of Technology, Faculty of Automotive and Construction Machinery Engineering, Warsaw, Poland Author https://orcid.org/0000-0002-0721-1105
Aldona Kluczek Warsaw University of Technology, Faculty of Mechanical and Industrial Engineering, Warsaw, Poland Author https://orcid.org/0000-0002-0156-4604

DOI:

https://doi.org/10.61089/aot2024.1mrj1x75

Keywords:

AFIR, electric vehicles charging stations, law-based method, TEN-T core network

Abstract

With the upcoming implementation of the amendment to Regulation (EU) 2019/631 of the European Parliament and of the Council, from 2035 there will be a ban on the registration of new vehicles with internal combustion engines (ICE) in the Member States of the European Union (EU). Consequently, changes in the transportation sector, resulting from the increasing use of electric vehicles, appear to be inevitable. According to the adopted legal acts, the European Union Member States will be obliged to develop, among others, a charging infrastructure and access to public charging stations for electric vehicles. As a result, there will be a need to ensure a significant increase in the power and the number of charging stations and to determine their appropriate location. The article presents the challenges faced by charging station operators and difficulties related to the further development of electric vehicle charging infrastructure in Poland. The still poorly developed public charging infrastructure for electric vehicles, especially in service areas located along the main communication routes, remains the main obstacle to the development of electromobility. In the context of legal, financial, technological, and organizational challenges, the problem of the proper distribution of electric vehicle charging stations along the main communication routes is therefore of particular importance. The aim of the article is to present a new, proprietary method for determining the location of electric vehicle charging stations in Poland within the Trans-European Transport Network (TEN-T), which considers objective location factors: adherence to AFIR requirements, the specificity of the Polish power system and existing parking infrastructure. As a result of using the developed method, a list of 188 recommended locations for the construction of electric vehicle charging stations in Poland along the Trans-European Transport Network (TEN-T) was created. It has been shown in this way that the use of the presented method enables the suitable determination of the location of electric vehicle charging stations along transport routes, considering legal, financial, and technological requirements, which will significantly facilitate the operation of zero-emission transport.

References

Abdel-Basset, M., Gamal, A., Hezam, I. M., & Sallam, K. M. (2023). Sustainability assessment of optimal location of electric vehicle charge stations: A conceptual framework for green energy into smart cities. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-023-03373-z.

Brdulak, A., Chaberek, G., & Jagodziński, J. (2020). Development Forecasts for the Zero-Emission Bus Fleet in Servicing Public Transport in Chosen EU Member Countries. Energies, 13(16), Article 16. https://doi.org/10.3390/en13164239.

Chmielewski, A., Piórkowski, P., Możaryn, J., & Ozana, S. (2023). Sustainable Development of Operational Infrastructure for Electric Vehicles: A Case Study for Poland. Energies, 16(11), Article 11. https://doi.org/10.3390/en16114528.

Church, R., & Velle, C. R. (1974). The Maximal Covering Location Problem. Papers in Regional Science, 32(1), 101–118. https://doi.org/10.1111/j.1435-5597.1974.tb00902.x.

Csiszár, C., Csonka, B., Földes, D., Wirth, E., & Lovas, T. (2020). Location optimisation method for fast-charging stations along national roads. Journal of Transport Geography, 88, 102833. https://doi.org/10.1016/j.jtrangeo.2020.102833.

Danese, A., Torsæter, B. N., Sumper, A., & Garau, M. (2022). Planning of High-Power Charging Stations for Electric Vehicles: A Review. Applied Sciences, 12(7), Article 7. https://doi.org/10.3390/app12073214.

Dominika, & Stankowska, A. (2021). European Union’s Goals Towards Electromobility: An Assessment of Plans’ Implementation in Polish Cities. European Research Studies Journal, XXIV, 645–665. https://doi.org/10.35808/ersj/2613.

Efthymiou, D., Chrysostomou, K., Morfoulaki, M., & Aifantopoulou, G. (2017). Electric vehicles charging infrastructure location: A genetic algorithm approach. European Transport Research Review, 9(2), Article 2. https://doi.org/10.1007/s12544-017-0239-7.

European Commission. (2022). Transport and the Green Deal. https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/european-green-deal/transport-and-green-deal_en.

European Commission. (2023). Trans-European Transport Network (TEN-T). https://transport.ec.europa.eu/transport-themes/infrastructure-and-investment/trans-european-transport-network-ten-t_en.

European Parliament. (2023). EUR-Lex—32023R1804—EN - EUR-Lex. https://eur-lex.europa.eu/eli/reg/2023/1804/oj.

Fit for 55. (2022, October 27). Deal confirms zero-emissions target for new cars and vans in 2035 | News | European Parliament. https://www.europarl.europa.eu/news/en/press-room/20221024IPR45734/deal-confirms-zero-emissions-target-for-new-cars-and-vans-in-2035.

Frade, I., Ribeiro, A., Gonçalves, G., & Pais Antunes, A. (2011). An optimization model for locating electric vehicle charging stations in central urban areas. Transp. Res. Rec., 3582, 1–19.

Gallo, M., & Marinelli, M. (2020). Sustainable Mobility: A Review of Possible Actions and Policies. Sustainability, 12(18), Article 18. https://doi.org/10.3390/su12187499.

Ghosh, A. (2021). Electric Vehicles—Solution toward Zero Emission from the Transport Sector. World Electric Vehicle Journal, 12(4), Article 4. https://doi.org/10.3390/wevj12040262.

Gong, L., Fu, Y., & Li, Z. (2016). Integrated planning of BEV public fast-charging stations. The Electricity Journal, 29(10), 62–77. https://doi.org/10.1016/j.tej.2016.11.010.

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.

Hodgson, M. J. (1990). A Flow-Capturing Location-Allocation Model. Geographical Analysis, 22(3), 270–279. https://doi.org/10.1111/j.1538-4632.1990.tb00210.x.

Holzwarth, S. (2015). Analysis of the transport relevance of each of the 17 SDGs. United Nations, 20.

Hussain, Z., Raza, S. H., & Shaheen, W. (2020). Trade, Infrastructure and Geography: An Application of Gravity Model on Asian Economies. Rivista Internazionale Di Economia Dei Transporti / International Journal of Transport Economics, 47, 145–169. https://doi.org/10.19272/202006702003.

Jochem, P., Szimba, E., & Reuter-Oppermann, M. (2019). How many fast-charging stations do we need along European highways? Transportation Research Part D: Transport and Environment, 73, 120–129. https://doi.org/10.1016/j.trd.2019.06.005.

Ju, Y., Ju, D., Santibanez Gonzalez, E. D. R., Giannakis, M., & Wang, A. (2019). Study of site selection of electric vehicle charging station based on extended GRP method under picture fuzzy environment. Computers & Industrial Engineering, 135, 1271–1285. https://doi.org/10.1016/j.cie.2018.07.048.

Kene, R., Olwal, T., & van Wyk, B. J. (2021). Sustainable Electric Vehicle Transportation. Sustainability, 13(22), Article 22. https://doi.org/10.3390/su132212379.

Kong, F., & Liu, X. (2017). Sustainable Transportation with Electric Vehicles. Foundations and Trends® in Electric Energy Systems, 2(1), 1-132 https://doi.org/10.1561/9781680833898.

LaMonaca, S., & Ryan, L. (2022). The state of play in electric vehicle charging services – A review of infrastructure provision, players, and policies. Renewable and Sustainable Energy Reviews, 154, 111733. https://doi.org/10.1016/j.rser.2021.111733.

Mock, P., & Diaz, S. (2021). Pathways to decarbonization: The European passenger car market, 2021–2035. White Paper. https://theicct.org/wp-content/uploads/2021/06/decarbonize-EU-PVs-may2021.pdf.

Napoli, G., Polimeni, A., Micari, S., Andaloro, L., & Antonucci, V. (2020). Optimal allocation of electric vehicle charging stations in a highway network: Part 1. Methodology and test application. Journal of Energy Storage, 27, 101102. https://doi.org/10.1016/j.est.2019.101102.

Pamucar, D., Ecer, F., & Deveci, M. (2021). Assessment of alternative fuel vehicles for sustainable road transportation of United States using integrated fuzzy FUCOM and neutrosophic fuzzy MARCOS methodology. Science of The Total Environment, 788, 147763. https://doi.org/10.1016/j.scitotenv.2021.147763.

PSPA. (2022). Poland drives e-mobility. Commissioned by the Netherlands Enterprise Agency. https://www.rvo.nl/files/file/2022-09/Poland-drives-e-mobility-report.pdf.

Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009.

Saaty, T. L. (1990). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. RWS Publications.

Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98. https://doi.org/10.1504/IJSSci.2008.01759.

Sadeghi-Barzani, P., Rajabi-Ghahnavieh, A., & Kazemi-Karegar, H. (2014). Optimal fast charging station placing and sizing. Applied Energy, 125, 289–299. https://doi.org/10.1016/j.apenergy.2014.03.077.

Sałabun, W., & Karczmarczyk, A. (2018). Using the COMET Method in the Sustainable City Transport Problem: An Empirical Study of the Electric Powered Cars. Procedia Computer Science, 126, 2248–2260. https://doi.org/10.1016/j.procs.2018.07.224.

Shirmohammadli, A., & Vallée, D. (2017). Developing a location model for fast charging infrastructure in urban areas. International Journal of Transport Development and Integration, 1(2), 159–170. https://doi.org/10.2495/TDI-V1-N2-159-170.

Sohail, M. T., Ullah, S., Majeed, M. T., & Usman, A. (2021). Pakistan management of green transportation and environmental pollution: A nonlinear ARDL analysis. Environmental Science and Pollution Research, 28(23), 29046–29055. https://doi.org/10.1007/s11356-021-12654-x.

Tian, Z., Hou, W., Gu, X., Gu, F., & Yao, B. (2018). The location optimization of electric vehicle charging stations considering charging behavior. Simulation, 94(7), 625–636. https://doi.org/10.1177/0037549717743807.

Upchurch, C., & Kuby, M. (2010). Comparing the p-median and flow-refueling models for locating alternative-fuel stations. Journal of Transport Geography, 18(6), 750–758. https://doi.org/10.1016/j.jtrangeo.2010.06.015.

Wang, J., Nie, R., Zhang, H., & Chen, X. (2013). Intuitionistic fuzzy multi-criteria decision-making method based on evidential reasoning. Applied Soft Computing, 13(4), 1823–1831. https://doi.org/10.1016/j.asoc.2012.12.019.

Wu, Y., Xie, C., Xu, C., & Li, F. (2017). A Decision Framework for Electric Vehicle Charging Station Site Selection for Residential Communities under an Intuitionistic Fuzzy Environment: A Case of Beijing. Energies, 10(9), Article 9. https://doi.org/10.3390/en10091270.

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), Article 3. https://doi.org/10.3390/en9030157.

Xiao, D., An, S., Cai, H., Wang, J., & Cai, H. (2020). An optimization model for electric vehicle charging infrastructure planning considering queuing behavior with finite queue length. Journal of Energy Storage, 29, 101317. https://doi.org/10.1016/j.est.2020.101317.

Yi, Z., & Bauer, P. H. (2016). Optimization models for placement of an energy-aware electric vehicle charging infrastructure. Transportation Research Part E: Logistics and Transportation Review, 91, 227–244. https://doi.org/10.1016/j.tre.2016.04.013.

Zhang, X., Jin, F., & Liu, P. (2013). A grey relational projection method for multi-attribute decision making based on intuitionistic trapezoidal fuzzy number. Applied Mathematical Modelling, 37(5), 3467–3477. https://doi.org/10.1016/j.apm.2012.08.012.

Zhao, J., Huang, L., Lv, X., Wang, J., & Yin, J. (2020). Optimization Model of Electric Vehicle Charging Station Layout. CICTP 2020, 1269–1280. https://doi.org/10.1061/9780784482933.109.

Zhou, G., Zhu, Z., & Luo, S. (2022). Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm. Energy, 247, 123437. https://doi.org/10.1016/j.energy.2022.123437.

Ziemba, P. (2021). Selection of Electric Vehicles for the Needs of Sustainable Transport under Conditions of Uncertainty—A Comparative Study on Fuzzy MCDA Methods. Energies, 14(22), Article 22. https://doi.org/10.3390/en14227786.