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A multi-criteria decision method for performance evaluation of public charging service quality

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  • Zhang, Lihui
  • Zhao, Zhenli
  • Yang, Meng
  • Li, Songrui

Abstract

Public electric vehicle charging infrastructure provides an essential support for sustainable electric transportation systems. However, the current development model for such infrastructure tends to emphasize quantity over quality and cannot meet the charging needs of electric vehicle users. Addressing this situation requires further guidance from governments, which should be based on performance evaluation systems. This study therefore developed a multi-criteria evaluation framework to assess the performance of public charging infrastructure in terms of planning rationality, operational efficiency, service capacity, charging safety, and sustainable development. After defining individual charging station attributes through numerical data and user/expert input, a modified Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model was used, with vague sets to standardize, weight, and process the data. The assessed stations were subsequently ranked. The model was applied to three public charging stations in Beijing, China to verify its effectiveness and robustness. The resulting rankings can facilitate regulatory assessment of these stations’ performance and guide improvements in the quality of their charging services. The results further indicated that the sustainable development value of charging facilities is often undervalued, and relevant incentive strategies should thus be implemented by policymakers.

Suggested Citation

  • Zhang, Lihui & Zhao, Zhenli & Yang, Meng & Li, Songrui, 2020. "A multi-criteria decision method for performance evaluation of public charging service quality," Energy, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:energy:v:195:y:2020:i:c:s0360544220300657
    DOI: 10.1016/j.energy.2020.116958
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    as
    1. Motoaki, Yutaka & Shirk, Matthew G., 2017. "Consumer behavioral adaption in EV fast charging through pricing," Energy Policy, Elsevier, vol. 108(C), pages 178-183.
    2. Neaimeh, Myriam & Salisbury, Shawn D. & Hill, Graeme A. & Blythe, Philip T. & Scoffield, Don R. & Francfort, James E., 2017. "Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles," Energy Policy, Elsevier, vol. 108(C), pages 474-486.
    3. Campíñez-Romero, Severo & Colmenar-Santos, Antonio & Pérez-Molina, Clara & Mur-Pérez, Francisco, 2018. "A hydrogen refuelling stations infrastructure deployment for cities supported on fuel cell taxi roll-out," Energy, Elsevier, vol. 148(C), pages 1018-1031.
    4. Ji, Zhenya & Huang, Xueliang, 2018. "Plug-in electric vehicle charging infrastructure deployment of China towards 2020: Policies, methodologies, and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 710-727.
    5. Liu, Jin-peng & Zhang, Teng-xi & Zhu, Jiang & Ma, Tian-nan, 2018. "Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration," Energy, Elsevier, vol. 164(C), pages 560-574.
    6. Tao, Ye & Huang, Miaohua & Yang, Lan, 2018. "Data-driven optimized layout of battery electric vehicle charging infrastructure," Energy, Elsevier, vol. 150(C), pages 735-744.
    7. Mohammadzadeh Bina, Saeid & Jalilinasrabady, Saeid & Fujii, Hikari & Farabi-Asl, Hadi, 2018. "A comprehensive approach for wind power plant potential assessment, application to northwestern Iran," Energy, Elsevier, vol. 164(C), pages 344-358.
    8. Goebel, Christoph, 2013. "On the business value of ICT-controlled plug-in electric vehicle charging in California," Energy Policy, Elsevier, vol. 53(C), pages 1-10.
    9. Zhang, Qi & Li, Hailong & Zhu, Lijing & Campana, Pietro Elia & Lu, Huihui & Wallin, Fredrik & Sun, Qie, 2018. "Factors influencing the economics of public charging infrastructures for EV – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 500-509.
    10. Zhu, Lijing & Zhang, Qi & Lu, Huihui & Li, Hailong & Li, Yan & McLellan, Benjamin & Pan, Xunzhang, 2017. "Study on crowdfunding’s promoting effect on the expansion of electric vehicle charging piles based on game theory analysis," Applied Energy, Elsevier, vol. 196(C), pages 238-248.
    11. Yang, Libing & Ribberink, Hajo, 2019. "Investigation of the potential to improve DC fast charging station economics by integrating photovoltaic power generation and/or local battery energy storage system," Energy, Elsevier, vol. 167(C), pages 246-259.
    12. Ahmed Abdalrahman & Weihua Zhuang, 2017. "A Survey on PEV Charging Infrastructure: Impact Assessment and Planning," Energies, MDPI, vol. 10(10), pages 1-25, October.
    13. Liu, Jian, 2012. "Electric vehicle charging infrastructure assignment and power grid impacts assessment in Beijing," Energy Policy, Elsevier, vol. 51(C), pages 544-557.
    14. Guo, Sen & Zhao, Huiru, 2015. "Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective," Applied Energy, Elsevier, vol. 158(C), pages 390-402.
    15. Ren, Xianqiang & Zhang, Huiming & Hu, Ruohan & Qiu, Yueming, 2019. "Location of electric vehicle charging stations: A perspective using the grey decision-making model," Energy, Elsevier, vol. 173(C), pages 548-553.
    16. Wang, Yue & Shi, Jianmai & Wang, Rui & Liu, Zhong & Wang, Ling, 2018. "Siting and sizing of fast charging stations in highway network with budget constraint," Applied Energy, Elsevier, vol. 228(C), pages 1255-1271.
    17. Zenginis, Ioannis & Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2016. "Analysis and quality of service evaluation of a fast charging station for electric vehicles," Energy, Elsevier, vol. 112(C), pages 669-678.
    18. Petrović, Marijana & Bojković, Nataša & Stamenković, Mladen & Anić, Ivan, 2018. "Supporting performance appraisal in ELECTRE based stepwise benchmarking model," Omega, Elsevier, vol. 78(C), pages 237-251.
    19. Hernández, J.C. & Ruiz-Rodriguez, F.J. & Jurado, F., 2017. "Modelling and assessment of the combined technical impact of electric vehicles and photovoltaic generation in radial distribution systems," Energy, Elsevier, vol. 141(C), pages 316-332.
    20. Long, Rui & Lai, Xiaotian & Liu, Zhichun & Liu, Wei, 2019. "Pressure retarded osmosis: Operating in a compromise between power density and energy efficiency," Energy, Elsevier, vol. 172(C), pages 592-598.
    21. Wu, Yunna & Xu, Chuanbo & Zhang, Buyuan & Tao, Yao & Li, Xinying & Chu, Han & Liu, Fangtong, 2019. "Sustainability performance assessment of wind power coupling hydrogen storage projects using a hybrid evaluation technique based on interval type-2 fuzzy set," Energy, Elsevier, vol. 179(C), pages 1176-1190.
    22. Serradilla, Javier & Wardle, Josey & Blythe, Phil & Gibbon, Jane, 2017. "An evidence-based approach for investment in rapid-charging infrastructure," Energy Policy, Elsevier, vol. 106(C), pages 514-524.
    23. Erbaş, Mehmet & Kabak, Mehmet & Özceylan, Eren & Çetinkaya, Cihan, 2018. "Optimal siting of electric vehicle charging stations: A GIS-based fuzzy Multi-Criteria Decision Analysis," Energy, Elsevier, vol. 163(C), pages 1017-1031.
    24. Barbosa, Ailson de Souza & Shayani, Rafael Amaral & Oliveira, Marco Aurélio Gonçalves de, 2018. "A multi-criteria decision analysis method for regulatory evaluation of electricity distribution service quality," Utilities Policy, Elsevier, vol. 53(C), pages 38-48.
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    7. Cristina Sousa & Evaldo Costa, 2022. "Types of Policies for the Joint Diffusion of Electric Vehicles with Renewable Energies and Their Use Worldwide," Energies, MDPI, vol. 15(20), pages 1-19, October.

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