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Hydrogen storage station location selection in sustainable freight transportation via intuitionistic hesitant decision support system

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  • Kokkinos, Konstantinos
  • Nathanail, Eftihia
  • Gerogiannis, Vassilis
  • Moustakas, Konstantinos
  • Karayannis, Vayos

Abstract

Increasingly fierce competition in energy industry for alternative fuels has raised demand for fuel storage stations to be one of the pivots towards sustainable urban freight transportation. For zero-emission hydrogen-powered vehicles, these demands focus mostly on storage capacity and refueling-station location selection to maximize freight forwarding efficiency in major urban regions. This research proposes a Decision Support System (DSS) for hydrogen storage station location selection based on Intuitionistic Hesitant Fuzzy (IHF) methodologies. An ensemble of four methods were analyzed and applied for the use case of Larissa city urban region, central Greece. Fifteen evaluation criteria were imposed by experts from the transportation department and the local competent authorities, spanning to hydrogen infrastructure, socioeconomics and fleet and road network. Scenarios such as energy efficiency, pollution prevention and public acceptance in conjunction to the risk and safety considerations play a critical role in the process. All qualitative indicators were represented by triangular intuitionistic fuzzy numbers. The ensemble produced the same ranking indicating the Steiner point locations of the imposed communication tree on the road network as the most preferable scenario.

Suggested Citation

  • Kokkinos, Konstantinos & Nathanail, Eftihia & Gerogiannis, Vassilis & Moustakas, Konstantinos & Karayannis, Vayos, 2022. "Hydrogen storage station location selection in sustainable freight transportation via intuitionistic hesitant decision support system," Energy, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:energy:v:260:y:2022:i:c:s0360544222019053
    DOI: 10.1016/j.energy.2022.125008
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    1. Chen, Xiaoyuan & Pang, Zhou & Jiang, Shan & Zhang, Mingshun & Feng, Juan & Fu, Lin & Shen, Boyang, 2023. "A novel LH2/GH2/battery multi-energy vehicle supply station using 100% local wind energy: Technical, economic and environmental perspectives," Energy, Elsevier, vol. 270(C).
    2. Woon, Kok Sin & Phuang, Zhen Xin & Taler, Jan & Varbanov, Petar Sabev & Chong, Cheng Tung & Klemeš, Jiří Jaromír & Lee, Chew Tin, 2023. "Recent advances in urban green energy development towards carbon emissions neutrality," Energy, Elsevier, vol. 267(C).
    3. Zhiming Lu & Youting Li, 2023. "A Multi-Criteria Framework for Sustainability Evaluation of Hydrogen-Based Multi-Microgrid Systems under Triangular Intuitionistic Fuzzy Environment," Sustainability, MDPI, vol. 15(4), pages 1-18, February.

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