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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.
Details
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
; Fang Sidun 2 ; Zhang Shenxi 3 ; Hu, Hao 1 1 State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; [email protected] (S.G.); [email protected] (Y.W.); [email protected] (M.Y.); [email protected] (H.H.), School of Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
2 School of Electrical Engineering, Chongqing University, Chongqing 400044, China; [email protected]
3 School of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; [email protected]