Optimization of Energy Replenishment for Inland Electric Ships Considering Multi-Technology Adoption and Partial Replenishment

While battery-powered propulsion represents a promising pathway for inland waterway freight, its widespread adoption is hindered by range anxiety and high investment costs. Strategic energy replenishment has emerged as a critical and cost-effective solution to extend voyage endurance and mitigate these barriers. This paper introduces a novel approach to optimize energy replenishment strategies for inland electric ships that considers the possibility of adopting multiple technologies (charging and battery swapping) and partial replenishment. The proposed approach not only identifies optimal replenishment ports but also determines the technology to employ and the corresponding amount of energy to replenish for each operation, aimed at minimizing total replenishment costs. This problem is formulated as a mixed-integer linear programming model. A case study of a 700-TEU electric container ship operating on two routes along the Yangtze River validates the effectiveness of the proposed approach. The methodology demonstrates superior performance over existing approaches by significantly reducing replenishment costs and improving solution feasibility, particularly in scenarios with tight schedules and limited technology availability. Furthermore, a sensitivity analysis examines the impacts of key parameters, offering valuable strategic insights for industry stakeholders.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-11-03
DOI
https://doi.org/10.3390/jmse13112092
Citations
1
Primary Topic
Maritime Transport Emissions and Efficiency
Type
article
Field-Weighted Citation Impact
0.80
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article

Optimization of Energy Replenishment for Inland Electric Ships Considering Multi-Technology Adoption and Partial Replenishment

Siqing Guo, Sidun Fang, Lei Dai, Shenxi Zhang et al.
1 citations
Journal of Marine Science and Engineering
Maritime Transport Emissions and Efficiency
0.80
article

Optimization of Energy Replenishment for Inland Electric Ships Considering Multi-Technology Adoption and Partial Replenishment

Siqing Guo, Sidun Fang, Lei Dai, Shenxi Zhang, Hao Hu, Mingyuan Yue, Yubing Wang
article en
1 citations

Abstract

While battery-powered propulsion represents a promising pathway for inland waterway freight, its widespread adoption is hindered by range anxiety and high investment costs. Strategic energy replenishment has emerged as a critical and cost-effective solution to extend voyage endurance and mitigate these barriers. This paper introduces a novel approach to optimize energy replenishment strategies for inland electric ships that considers the possibility of adopting multiple technologies (charging and battery swapping) and partial replenishment. The proposed approach not only identifies optimal replenishment ports but also determines the technology to employ and the corresponding amount of energy to replenish for each operation, aimed at minimizing total replenishment costs. This problem is formulated as a mixed-integer linear programming model. A case study of a 700-TEU electric container ship operating on two routes along the Yangtze River validates the effectiveness of the proposed approach. The methodology demonstrates superior performance over existing approaches by significantly reducing replenishment costs and improving solution feasibility, particularly in scenarios with tight schedules and limited technology availability. Furthermore, a sensitivity analysis examines the impacts of key parameters, offering valuable strategic insights for industry stakeholders.

Journal of Marine Science and EngineeringVol. 13(11)
Chongqing University (CN), Shanghai Jiao Tong University (CN), Shanghai Ocean University (CN)
Openalex Percentile: Top 23%
Maritime Transport Emissions and Efficiency
0.80
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Optimization of Energy Replenishment for Inland Electric Ships Considering Multi-Technology Adoption and Partial Replenishment — Siqing Guo, Sidun Fang, et al. · Journal of Marine Science and Engineering (2025) | TGRS Research Map | TGRS