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Site Selection Decision-Making for Offshore Wind-to-Hydrogen Production Bases Based on the Two-Dimensional Linguistic Cloud Model

Author

Listed:
  • Chen Fu

    (State Grid Shanghai Economic Research Institute, Shanghai 200235, China)

  • Li Lan

    (State Grid Shanghai Economic Research Institute, Shanghai 200235, China)

  • Su Chen

    (State Grid Shanghai Economic Research Institute, Shanghai 200235, China)

  • Mingxing Guo

    (State Grid Shanghai Economic Research Institute, Shanghai 200235, China)

  • Xiaojing Jiang

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

  • Xiaoran Yin

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

  • Chuanbo Xu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, Beijing 102206, China)

Abstract

Offshore wind-to-hydrogen production is an effective means of solving the problems of large-scale grid-connected consumption and high power transmission costs of offshore wind power. Site selection is a core component in planning offshore wind-to-hydrogen facilities, involving careful consideration of multiple factors, and is a classic multi-criteria decision-making problem. Therefore, this study proposes a multi-criteria decision-making method based on the two-dimensional linguistic cloud model to optimize site selection for offshore wind-to-hydrogen bases. Firstly, the alternative schemes are evaluated using two-dimensional linguistic information, and a new model for transforming two-dimensional linguistic information into a normal cloud is constructed. Then, the cloud area overlap degree is defined to calculate the interaction factor between decision-makers, and a multi-objective programming model based on maximum deviation-minimum correlation is established. Following this, the Pareto solution of criteria weights is solved using the non-dominated sorting genetic algorithm II, and the alternatives are sorted and selected through the cloud-weighted average operator. Finally, an index system was constructed in terms of resource conditions, planning conditions, external conditions, and other dimensions, and a case study was conducted using the location of offshore wind-to-hydrogen production bases in Shanghai. The method proposed in this study demonstrates strong robustness and can provide a basis for these multi-criteria decision-making problems with solid qualitative characteristics.

Suggested Citation

  • Chen Fu & Li Lan & Su Chen & Mingxing Guo & Xiaojing Jiang & Xiaoran Yin & Chuanbo Xu, 2024. "Site Selection Decision-Making for Offshore Wind-to-Hydrogen Production Bases Based on the Two-Dimensional Linguistic Cloud Model," Energies, MDPI, vol. 17(20), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5203-:d:1502040
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    References listed on IDEAS

    as
    1. Shu Zhang & Wenying Chen, 2022. "Assessing the energy transition in China towards carbon neutrality with a probabilistic framework," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Farhad Taghizadeh-Hesary & Naoyuki Yoshino, 2020. "Sustainable Solutions for Green Financing and Investment in Renewable Energy Projects," Energies, MDPI, vol. 13(4), pages 1-18, February.
    3. Shaojie Song & Haiyang Lin & Peter Sherman & Xi Yang & Chris P. Nielsen & Xinyu Chen & Michael B. McElroy, 2021. "Production of hydrogen from offshore wind in China and cost-competitive supply to Japan," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    4. Xinyang Guo & Xinyu Chen & Xia Chen & Peter Sherman & Jinyu Wen & Michael McElroy, 2023. "Grid integration feasibility and investment planning of offshore wind power under carbon-neutral transition in China," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

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