A Comparison of Different Multi-Criteria Analyses for Electric Vehicle Charging Station Deployment

Authors

  • Babak Daneshvar Rouyendegh (B. Erdebilli) Department of Industrial Engineering, Ankara Yıldırım Beyazıt University, Ankara
  • Cem Isik Dogru Department of Industrial Engineering, TOBB Economy and Technology University, 06510 Ankara
  • Canan Basak Aybirdi Department of Industrial Engineering, TOBB Economy and Technology University, 06510 Ankara

DOI:

https://doi.org/10.26713/cma.v10i1.1126

Keywords:

AHP, VIKOR, TOPSIS, Electric vehicles, Integer programming

Abstract

Scarcity in near future, and the price fluctuation of fossil fuels lead to many industries change their products that use these resources into more eco-friendly versions. One of the most recent and noticeable example of this situation is the automobile industry. As a result of this, electric vehicles have started to become more popular and their sales increase substantially. Since these electric vehicles have a limited range for transportation before they require charging, the number and the positions of charging units become very important. In this study, we consider a electric vehicle (EV) charging station (CS) placement problem which aims to maximize users' utility. To deal with these problem, we survey to find the weights of criterion, which are selected as accessibility, traffic convenience and waiting time calculated by AHP method and VIKOR and TOPSIS methods are used to evaluate each alternative. As a main tool for charging station deployment, an integer programming model, which maximizes electric vehicle driver's utility in term of evaluation results, is developed and the effects of different evaluation techniques on deployment procedure is shown and compared.

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References

T. Boden, R. Andres and G. Marland, Global, regional, and national fossil fuel CO2 emissions (1751-2014) (v. 2017), Technical Report, Carbon Dioxide Information Analysis Center (CDIAC), Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States), (2017), DOI: 10.3334/CDIAC/00001_V2017.

British Petroleum Company, BP Statistical Review of World Energy 2018, http://www.indiaenvironmentportal.org.in/files/file/bp-stats-review-2018-full-report.pdf

S.-J. Chen and C.-L. Hwang, Fuzzy multiple attribute decision making methods, in Fuzzy Multiple Attribute Decision Making, pp. 289 – 486, Springer (1992), DOI: 10.1007/978-3-642-46768-4_5.

M. Erba¸s, M. Kabak, E. í–zceylan and C. í‡etinkaya, Optimal siting of electric vehicle charging stations: A GIS-based fuzzy multi-criteria decision analysis, Energy 163 (2018), 1017 – 1031, DOI: 10.1016/j.energy.2018.08.140.

E.U. Ergul, A. Yildiz and L. Ugur, The best vehicle engine system selection using vikor and topsis methods, in International Conference on Engineering and Natural Sciences (ICENS) 2016, pages 1217-1223, https://www.researchgate.net/publication/314950185 (2016)

A. Fan and C. Yang„ Optimal site selection of electric vehicle charging station based on fuzzy AHP-TOPSIS, in Production and Operations Management Conference 27th Annual Meeting, May 6-9, 2016, Orlando, FL, USA, https://www.pomsmeetings.org/ConfProceedings/065/Full%20Papers/Final%20Full%20Papers/065-0074.pdf.

C. Feng, B. Zhou, N. Lin, Y. Li and Y. Xia, Application of comprehensive evaluation method integrating delphi and gahp inoptimal siting of electric vehicle charging station, Electric Power Automation Equipment 32(9) (2012), 25 – 29, https://www.researchgate.net/publication/279707511.

M.E. Genevois and H. Kocaman, Locating electric vehicle charging stations in istanbul with ahp based mathematicalmodelling, International Journal of Transportation Systems 3 (2018), 1 – 10, https://www.iaras.org/iaras/filedownloads/ijts/2018/019-0001(2018).pdf

S. Guo and H. Zhao, Optimal site selection of electric vehicle charging station by using fuzzy topsis based on sustainability perspective, Applied Energy 158 (2015), 390 – 402, DOI: 10.1016/j.apenergy.2015.08.082.

C.-L. Hwang and K. Yoon, Methods for multiple attribute decision making, in Multiple Attribute Decision Making, pp. 58 – 191, Springer (1981), DOI: https://doi.org/10.1007/978-3-642-48318-9_3.

International Energy Agency, Electric car share in the SDS, https://www.iea.org/tcep/transport/evs/, accessed on October 1, 2018.

International Monetary Fund, Global price of Brent Crude [poilbreusda], retrieved from FRED, Federal Reserve Bank of St. Louis, https://fred.stlouisfed.org/series/POILBREUSDA, October 01, 2018.

A. Janjic, L. Velimirovic, M. Stankovic, Ž. Džunic and J. Ranitovic, Multi-criteria decision methodology for the optimization of public electric vehicle charging infrastructure, in The Sixth International Conference Transport and Logistics, pp. 283 – 286, (2017), https://www.researchgate.net/publication/317278752.

H.-C. Liu, M. Yang, M. Zhou and G. Tian, An integrated multi-criteria decision making approach to location planning of electric vehicle charging stations, IEEE Transactions on Intelligent Transportation Systems 20(1) (2018), 362 – 373, https://doi.org/10.1109/TITS.2018.2815680.

J. Liu and Q. Wei, Risk evaluation of electric vehicle charging infrastructure public-private partnership projects in china using fuzzy TOPSIS, Journal of Cleaner Production 189 (2018), 211 – 222, DOI: https://doi.org/10.1016/j.jclepro.2018.04.103.

S. Opricovic, Multicriteria optimization of civil engineering systems, Faculty of Civil Engineering, Belgrade 2(1) (1998), 5 – 21.

S. Opricovi and G.H. Tzeng, Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research 156(2) (2004), 445 – 455, DOI: 10.1016/S0377-2217(03)00020-1.

J. Raposo, A. Rodrigues, C. Silva and T. Dentinho, A multi-criteria decision aid methodology to design electric vehicles public charging networks, AIP Advances 5(5) (2015), 057123.

B.D. Rouyendegh, U. Bac and T.E. Erkan„ Sector selection for ERP implementation to achieve most impact on supply chain performance by using AHP-TOPSIS hybrid method, Tehnicki Vjesnik-Technical Gazette 21(5) (2014), 933 – 937, https://www.researchgate.net/publication/269397241.

B.D. Rouyendegh, K. Topuz, A. Dag and A. Oztekin, An AHP-IFT integrated model for performance evaluation of ecommerce web sites, Information Systems Frontiers (2018), 1 – 11, DOI: 10.1007/s10796-018-9825-z.

T.L. Saaty, How to make a decision:the analytic hierarchy process, European Journal of Operational Research 48(1) (1990), 9 – 26, DOI: 10.1016/0377-2217(90)90057-I.

G.-H. Tzeng and J.-J. Huang, Multiple Attribute Decision Making: Methods and Applications, Chapman and Hall/CRC (2011).

G.-H. Tzeng, C.-W. Lin and S. Opricovic, Multi-criteria analysis of alternative-fuel buses for public transportation, Energy Policy 33(11) (2005), 1373 – 1383, DOI: 10.1016/j.enpol.2003.12.014.

Y. Wu, M. Yang, H. Zhang, K. Chen and Y. Wang, Optimal site selection of electric vehicle charging stations based on a cloud model and the Promethee method, Energies 9(3) (2016), 157, DOI: 10.1016/j.enpol.2003.12.014.

B. Ya˘gcitekin, M. Uzuno˘glu and A. Karaka¸s, Anew deployment method for electric vehicle charging infrastructure, Turkish Journal of Electrical Engineering & Computer Sciences 24(3) (2016), 1292 – 1305, http://journals.tubitak.gov.tr/elektrik/issues/elk-16-24-3/elk-24-3-43-1311-221.pdf.

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Published

31-03-2019
CITATION

How to Cite

Rouyendegh (B. Erdebilli), B. D., Dogru, C. I., & Aybirdi, C. B. (2019). A Comparison of Different Multi-Criteria Analyses for Electric Vehicle Charging Station Deployment. Communications in Mathematics and Applications, 10(1), 145–158. https://doi.org/10.26713/cma.v10i1.1126

Issue

Vol. 10 No. 1 (2019)

Section

Research Article

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