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Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method

Author

Listed:
  • Yunna Wu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Meng Yang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Haobo Zhang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Kaifeng Chen

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Yang Wang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

The task of site selection for electric vehicle charging stations (EVCS) is hugely important from the perspective of harmonious and sustainable development. However, flaws and inadequacies in the currently used multi-criteria decision making methods could result in inaccurate and irrational decision results. First of all, the uncertainty of the information cannot be described integrally in the evaluation of the EVCS site selection. Secondly, rigorous consideration of the mutual influence between the various criteria is lacking, which is mainly evidenced in two aspects: one is ignoring the correlation, and the other is the unconscionable measurements. Last but not least, the ranking method adopted in previous studies is not very appropriate for evaluating the EVCS site selection problem. As a result of the above analysis, a Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) method-based decision system combined with the cloud model is proposed in this paper for EVCS site selection. Firstly, the use of the PROMETHEE method can bolster the confidence and visibility for decision makers. Secondly, the cloud model is recommended to describe the fuzziness and randomness of linguistic terms integrally and accurately. Finally, the Analytical Network Process (ANP) method is adopted to measure the correlation of the indicators with a greatly simplified calculation of the parameters and the steps required.

Suggested Citation

  • Yunna Wu & Meng Yang & Haobo Zhang & Kaifeng Chen & Yang Wang, 2016. "Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method," Energies, MDPI, vol. 9(3), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:157-:d:64969
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