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Geographic information big data-driven two-stage optimization model for location decision of hydrogen refueling stations: An empirical study in China

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  • Zhou, Jianli
  • Wu, Yunna
  • Tao, Yao
  • Gao, Jianwei
  • Zhong, Zhiming
  • Xu, Chuanbo

Abstract

The promotion of hydrogen fuel cell vehicles (HFCVs) is an effective way to decarbonize the transportation industry. However, the shortage and difficulty in the layout of hydrogen refueling stations (HRSs) are the key obstacles to the HFCVs development. This paper constructs a two-stage location optimization model based on geographic information big data to provide technical support for the HRSs layout. The first stage is suitability analysis led by the geographic information system; the second is decision analysis based on the multi-criteria decision-making (MCDM) approach. First, the analysis elements and indicators used in the two-stage model are respectively given: including ten types of geographic information elements and six evaluation indicators. Then, the key steps and core algorithms of the two-stage model are introduced in detail. Thirdly, this paper takes the Weifang City of Shandong Province as the study area to carry out an empirical case to verify the model. The weight results show that traffic convenience is the key determinant of suitability (more than 25%); the economic development level and public acceptance of the alternative site area are the critical indicators in the decision-making stage (more than 25%). The model gives the suitability score for all available land in the study area. The suitability score is between 3.521 and 8.047 (10 points scale). Taking the median value of 5.784 as the threshold value, eight alternative sites are selected from the green areas suitable for layout based on the distribution of interest points, which are included in the planning for the next two years. The layout priority rankings show that alternative sites A1, A6, and A5 are ranked high. The reliability and uniqueness of the model are proved by comparative analysis. The results of sensitivity analysis and scenario analysis show that the sensitivity preference of decision-makers could significantly affect the priority ranking. The empirical study will provide effective reference and enlightenment for Shandong to develop hydrogen energy strategy.

Suggested Citation

  • Zhou, Jianli & Wu, Yunna & Tao, Yao & Gao, Jianwei & Zhong, Zhiming & Xu, Chuanbo, 2021. "Geographic information big data-driven two-stage optimization model for location decision of hydrogen refueling stations: An empirical study in China," Energy, Elsevier, vol. 225(C).
    • Handle: RePEc:eee:energy:v:225:y:2021:i:c:s036054422100579x
    DOI: 10.1016/j.energy.2021.120330
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    2. Zhao, Tian & Liu, Zhixin & Jamasb, Tooraj, 2022. "Developing hydrogen refueling stations: An evolutionary game approach and the case of China," Energy Economics, Elsevier, vol. 115(C).
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    4. Zhao, Tian & Liu, Zhixin & Jamasb, Tooraj, 2021. "Developing Hydrogen Infrastructure and Demand: An Evolutionary Game and the Case of China," Working Papers 18-2021, Copenhagen Business School, Department of Economics.
    5. Du, Zhengyang & Dai, Zhenxue & Yang, Zhijie & Zhan, Chuanjun & Chen, Wei & Cao, Mingxu & Thanh, Hung Vo & Soltanian, Mohamad Reza, 2024. "Exploring hydrogen geologic storage in China for future energy: Opportunities and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 196(C).
    6. Nithin Isaac & Akshay K. Saha, 2023. "A Review of the Optimization Strategies and Methods Used to Locate Hydrogen Fuel Refueling Stations," Energies, MDPI, vol. 16(5), pages 1-16, February.
    7. Wang, Yongli & Tao, Siyi & Chen, Xin & Huang, Feifei & Xu, Xiaomin & Liu, Xiaoli & Liu, Yang & Liu, Lin, 2022. "Method multi-criteria decision-making method for site selection analysis and evaluation of urban integrated energy stations based on geographic information system," Renewable Energy, Elsevier, vol. 194(C), pages 273-292.

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