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Distributionally robust scheduling of electric‑hydrogen integrated energy systems based on pipeline-road coordinated hydrogen transportation

Author

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  • Tan, Hong
  • Chen, Shun
  • Lin, Zhenjia
  • Wang, Qiujie
  • Mohamed, Mohamed A.

Abstract

Electrolytic water hydrogen production is an effective method for achieving the absorption of excess renewable energy and peak shaving and valley filling in the power system. However, when facing large-scale and long-distance hydrogen transportation needs, existing hydrogen transportation strategies struggle to transport hydrogen economically and flexibly from hydrogen production plants (HPPs) to various hydrogen users. To this end, this paper proposes a distributionally robust optimization (DRO) scheduling model for the electric‑hydrogen integrated energy system (EHIES) based pipeline-road collaborative hydrogen transportation (PRCHT). Firstly, by analyzing the transportation mechanism of hydrogen-blended pipelines and combining the relationship between the pipeline's storage and the gas pressure at both ends, this work constructs a quasi-dynamic transportation model for natural gas hydrogen blending with a variable hydrogen blending ratio. Next, by employing the improved McCormick technique and piecewise linearization method, the quasi-dynamic model is transformed into a mixed-integer linear programming (MILP) model. Furthermore, by integrating the trailer-based hydrogen transportation model, a PRCHT model is developed. Finally, considering the high uncertainty in wind power output, a DRO scheduling model for the integrated electricity‑hydrogen energy system based on Wasserstein distance is proposed. The DRO model is then transformed into a MILP problem using the conditional value-at-risk (CVaR) approximation method. The simulation results demonstrate that the proposed scheduling model reduces the total system cost by 19.43 % compared to the constant hydrogen blending ratio benchmark, while preventing 22.68 % of potential hydrogen load shedding relative to the natural-gas-pipeline-exclusive transport model. Meanwhile, the employed algorithm improves computational efficiency and achieves a robust optimization of the scheduling decisions by balancing system robustness and economic performance.

Suggested Citation

  • Tan, Hong & Chen, Shun & Lin, Zhenjia & Wang, Qiujie & Mohamed, Mohamed A., 2026. "Distributionally robust scheduling of electric‑hydrogen integrated energy systems based on pipeline-road coordinated hydrogen transportation," Applied Energy, Elsevier, vol. 404(C).
    • Handle: RePEc:eee:appene:v:404:y:2026:i:c:s0306261925017854
    DOI: 10.1016/j.apenergy.2025.127055
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    References listed on IDEAS

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    1. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "Distributionally robust operation for integrated rural energy systems with broiler houses," Energy, Elsevier, vol. 254(PC).
    2. Saedi, Isam & Mhanna, Sleiman & Mancarella, Pierluigi, 2021. "Integrated electricity and gas system modelling with hydrogen injections and gas composition tracking," Applied Energy, Elsevier, vol. 303(C).
    3. Tan, Hong & Li, Zhenxing & Wang, Qiujie & Mohamed, Mohamed A., 2023. "A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses," Applied Energy, Elsevier, vol. 330(PB).
    4. Miao, Huiying & Yu, Yadong & Wan, Yanming & Zhang, Yan & Ma, Tieju, 2024. "Levelized cost of long-distance large-scale transportation of hydrogen in China," Energy, Elsevier, vol. 310(C).
    5. Li, Yang & Han, Meng & Shahidehpour, Mohammad & Li, Jiazheng & Long, Chao, 2023. "Data-driven distributionally robust scheduling of community integrated energy systems with uncertain renewable generations considering integrated demand response," Applied Energy, Elsevier, vol. 335(C).
    6. Yi Yu & Guo-Ping Liu & Yi Huang & Chi Yung Chung & Yu-Zhong Li, 2024. "A blockchain consensus mechanism for real-time regulation of renewable energy power systems," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    7. Yamamoto, Hiromi & Fujioka, Hanako & Okano, Kunihiko, 2021. "Cost analysis of stable electric and hydrogen energy supplies derived from 100% variable renewable resources systems," Renewable Energy, Elsevier, vol. 178(C), pages 1165-1173.
    8. Han, Li & Wang, Shiqi & Cheng, Yingjie & Chen, Shuo & Wang, Xiaojing, 2024. "Multi-timescale scheduling of an integrated electric-hydrogen energy system with multiple types of electrolysis cells operating in concert with fuel cells," Energy, Elsevier, vol. 307(C).
    9. Du, Yida & Li, Xiangguang & Tan, Caixia & Tan, Zhongfu, 2024. "Two-stage multi-objective distributionally robust operation optimization and benefits equalization of an off-grid type electric-hydrogen-ammonia-methanol coupling system," Renewable Energy, Elsevier, vol. 236(C).
    10. Tan, Hong & Wang, Yuwei & Wang, Qiujie & Lin, Zhenjia & Mohamed, Mohamed A., 2024. "Day-ahead dispatch of electricity-hydrogen systems under solid-state transportation mode of hydrogen energy via FV-IGDT approach," Energy, Elsevier, vol. 300(C).
    11. Lou, Chengwei & Jin, Zekai & Zhou, Yue & Tang, Wei & Zhang, Lu & Yang, Jin, 2025. "Privacy-protected P2P electricity and carbon emission trading markets based on distributionally robust proximal atomic coordination algorithm," Applied Energy, Elsevier, vol. 384(C).
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