Hydrogen refueling station location optimization under uncertainty

Zhen, Lu; Wu, Jingwen; Yang, Zhiyuan; Ren, Yiran; Li, Wenxin

doi:10.1016/j.cie.2024.110068

Computers & Industrial Engineering

2024

DOI: 10.1016/j.cie.2024.110068

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Hydrogen refueling station location optimization under uncertainty

Lu Zhen,

Jingwen Wu,

Zhiyuan Yang

et al.

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2024

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Cited by 5 publications

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A mechanistic framework for the leakage risk reduction of mobile hydrogen refueling stations based on inherent safety concepts

Gao,

Chen,

et al. 2024

International Journal of Hydrogen Energy

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A mechanistic framework for the leakage risk reduction of mobile hydrogen refueling stations based on inherent safety concepts

Gao,

Chen,

et al. 2024

International Journal of Hydrogen Energy

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Deep learning-based hydrogen leakage localization prediction considering sensor layout optimization in hydrogen refueling stations

Wang,

Bi,

Shi

et al. 2024

Process Safety and Environmental Protection

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Attention-Based Hydrogen Refueling Imputation Model for Efficient Hydrogen Refueling Stations

Ko,

Kim

2024

Applied Sciences

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During hydrogen refueling, the data values determining the state of charge (SoC) of a vehicle can be missing due to internal and external factors. This causes inaccurate SoC estimation, resulting in oversupply or undersupply. To overcome this issue, an attention-based hydrogen refueling imputation (AHRI) model, which restores missing values, is proposed in this paper. In particular, considering that data variables can vary depending on the environmental conditions and equipment in a hydrogen refueling station (HRS), we use the attention mechanism. It determines the primary features, which improves the predictive performance and helps adapt to new conditions. Using the observed data during hydrogen refueling, we train the proposed AHRI model and verify its efficacy. Experimental results show that the proposed AHRI model outperforms existing imputation models significantly. Here, AHRI achieves 0.95 and 0.82 in terms of R2 when 20% and 40% of the values are missing, respectively. These results indicate that the proposed model can be used to solve the data missing problems in HSRs.

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Hydrogen refueling station location optimization under uncertainty

Cited by 5 publications

References 24 publications

A mechanistic framework for the leakage risk reduction of mobile hydrogen refueling stations based on inherent safety concepts

A mechanistic framework for the leakage risk reduction of mobile hydrogen refueling stations based on inherent safety concepts

Deep learning-based hydrogen leakage localization prediction considering sensor layout optimization in hydrogen refueling stations

Attention-Based Hydrogen Refueling Imputation Model for Efficient Hydrogen Refueling Stations

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