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

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Publicado en:Journal of Marine Science and Engineering vol. 13, no. 11 (2025), p. 2092-2118
Autor principal: Guo Siqing
Otros Autores: Wang, Yubing, Yue Mingyuan, Dai Lei, Fang Sidun, Zhang Shenxi, Hu, Hao
Publicado:
MDPI AG
Materias:
Linear programming
Integer programming
Ports
Sensitivity analysis
Parameter sensitivity
Electric vehicles
Optimization
Container ships
Ships
Energy consumption
Technology adoption
Energy
Energy costs
Cargo ships
Decision making
Flexibility
Effectiveness
Replenishment
Energy efficiency
Mixed integer
Inland waterways
Cost control
Inland waters
Economic
Acceso en línea:Citation/Abstract
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Resumen: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.
ISSN:2077-1312
DOI:10.3390/jmse13112092
Fuente:Engineering Database