基于作业能耗的港口新能源混合动力拖轮调度

初良勇, 林嘉辰, 黄先婷, 杜嘉音, 张一鸣

doi:10.16411/j.cnki.issn1006-7736.2025.02.008

大连海事大学学报 >

2025 , Vol. 51 >Issue 2: 66 - 76

DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2025.02.008

基于作业能耗的港口新能源混合动力拖轮调度

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(1. 集美大学航海学院，福建厦门 361021; 2.福建航运研究院，福建厦门 361021)

初良勇*（1973 — ），男，博士，教授，博士生导师，研究方向：智慧港口与智能物流、智慧供应链，E-mail：chuliangyong@163.com。林嘉辰（2000 — ），男，硕士生，研究方向：智慧港口与智能物流。黄先婷（2002 — ），女，硕士生，研究方向：智慧港口与智能物流。杜嘉音（2001 — ），女，硕士生，研究方向：智慧港口与智能物流。张一鸣（1998 — ），男，硕士生，研究方向：智慧港口与智能物流。

网络出版日期: 2025-04-18

基金资助

国家社会科学基金项目（24BGL282）

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Research on scheduling of port new energy hybrid tugboat based on operational energy consumption

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(1. Navigation Institute, Jimei University, Xiamen 361021, China; 2. Shipping Research Institute of Fujian Province, Xiamen 361021, China)

Online published: 2025-04-18

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摘要

为促进绿色港口建设，将新能源混合动力拖轮引入传统拖轮调度问题中，结合拖轮在不同作业工况下的能耗特点，构建以船舶在港总成本、拖轮作业产生的电耗成本与油耗成本之和最小为目标的混合动力拖轮调度混合整数线性规划模型。针对问题的特点设计了嵌入启发式规则的鲸鱼优化算法进行求解，在小规模算例时可以求出与Gurobi误差在0.00%至1.96%内的较优解。算例求解结果显示，通过优化调度混合动力拖轮可有效降低6.91%的拖轮作业总成本与20.80%的燃油消耗量；敏感性分析体现出总成本及油耗随混合动力拖轮数量、电池容量与单位时间充电量三种参数的增加呈现下降趋势，并且三种参数在合理范围内取值时可有效降低总成本。研究可为港口拖轮实际运营提供理论支撑与决策参考。

关键词： 拖轮调度; 新能源; 混合动力拖轮; 混合整数线性规划模型; 鲸鱼优化算法

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初良勇, 林嘉辰, 黄先婷, 杜嘉音, 张一鸣 .

基于作业能耗的港口新能源混合动力拖轮调度

[J]. 大连海事大学学报, 2025 , 51(2) : 66 -76 . DOI: 10.16411/j.cnki.issn1006-7736.2025.02.008

Abstract

To promote the development of green ports, new energy hybrid tugboats are introduced into the traditional tugboat scheduling problem. By incorporating the energy consumption characteristics of tugboats under different operational conditions, a mixed-integer linear programming model is formulated to minimize the total cost of port operations, including the combined electricity and fuel consumption costs of tugboat activities. A whale optimization algorithm embedded with heuristic rules is designed to solve the problem, which, when applied to small-scale examples, provides optimal solutions with errors ranging from 0.00% to 1.96% compared to the Gurobi solver. The case study results show that optimizing the scheduling of hybrid tugboats can effectively reduce the total tugboat operation costs by 6.91% and fuel consumption by 20.80%. The sensitivity analysis demonstrates that the total cost and fuel consumption decrease as the number of hybrid tugboats, battery capacity, and charging rate per unit time increase. Furthermore, when the values of these three parameters are within a reasonable range, they can effectively reduce the total cost. The research can provide theoretical support and decision-making reference for the actual operation of port tugboats.

Key words： tugboat scheduling; new energy; hybrid tugboat; mixed integer linear programming model; whale optimization algorithm

参考文献

[1] 李泽皓, 王甫, 胡卓, 等. 混合动力船舶能源配置与推进系统发展现状[J]. 大连海事大学学报, 2023, 49(3): 74-87.

LI Z H, WANG F, HU Z, YUAN J L. Current status of energy configuration and propulsion system development for hybrid power ships[J]. Journal of Dalian Maritime University, 2023, 49(3): 74-87. (in Chinese)

[2] 张圣超, 李亚楠, 王驰明, 等. 绿色混合动力拖轮现状及设计方案[J]. 机电设备, 2021, 38(6): 99-106; ZHANG S C, LI Y N, WANG C M, et al. Status and design scheme of green hybrid tugboat[J]. Mechanical and Electrical Equipment, 2021, 38(6): 99-106. (in Chinese)

[3] KARAÇAY Ö E, ÖZSOYSAL O A. Techno-economic investigation of alternative propulsion systems for tug-boats[J]. Energy Conversion and Management: X, 2021, 12: 100140.

[4] 胡敬梁, 刘云超, 孙烨. 油电混合拖轮能效及应用前景分析[J]. 船舶工程, 2023, 45(S1): 315-317+325.

HU J L, LIU Y C, SUN Y. Analysis on energy efficiency and application prospect of oil-electric hybrid tugs[J]. Ship engineering, 2023, 45(S1): 315-317+325. (in Chinese)

[5] 徐奇, 边展, 陈燕, 等. 多停泊基地约束下港口拖轮作业的一体化调度优化[J]. 上海交通大学学报, 2014, 48(1): 132-139+145.

XU Q, BIAN Z, CHEN Y, et al. Scheduling optimization of port tugboat operation considering multi-anchorage[J]. Journal of Shanghai Jiaotong University, 2014, 48(1): 132-139+145. (in Chinese)

[6] 刘志雄, 李俊, 邵正宇, 等. 拖轮动态调度的混合演化策略算法设计[J]. 计算机工程与设计, 2016, 37(2): 519-524+529.

LIU Z X, LI J, SHAO Z Y, et al. Design of hybrid evolu-tionary strategy algorithm of dynamic tugboat scheduling problem[J]. Computer Engineering and Design, 2016, 37(2): 519-524+529. (in Chinese)

[7] 蔡芸, 刘朋青, 熊禾根. 基于量子遗传混合算法的泊位联合调度[J]. 计算机应用, 2020, 40(3): 897-901.

CAI Y, LIU P Q, XIONG H G. Berth joint scheduling based on quantum genetic hybrid algorithm[J]. Journal of Com-puter Applications, 2020, 40(3): 897-901. (in Chinese)

[8] KANG L, MENG Q, Tan K C. Tugboat scheduling under ship arrival and tugging process time uncertainty[J]. Transportation Research Part E: Logistics and Transpor-tation Review, 2020, 144: 102125.

[9] 王巍, 赵宏, 李强. 面向多停泊基地的港口拖轮调度优化研究[J]. 计算机工程与应用, 2013, 49(13): 8-12+35;

WANG W, ZHAO H, LI Q. Multi-objectives optimization for port tugboat scheduling considering multi-anchorage bases[J]. Computer Engineering and Applications, 2013, 49(13): 8-12+35. (in Chinese)

[10] ZHONG H, ZHANG Y, GU Y. A Bi-objective green tug-boat scheduling problem with the tidal port time win-dows[J]. Transportation Research Part D: Transport and Environment, 2022, 110: 103409.

[11] LI B, CHEN Q, LAU Y, et al. Tugboat Scheduling with Multiple Berthing Bases under Uncertainty[J]. Journal of Marine Science and Engineering, 2023, 11(11): 2180.

[12] WANG X, LIANG Y, WEI X, et al. An adaptive large neighborhood search algorithm for the tugboat scheduling problem[J]. Computers & Industrial Engineering, 2023, 177: 109039.

[13] SUN C, LI M, CHEN L, et al. Dynamic Tugboat Scheduling for Large Seaports with Multiple Terminals[J]. Journal of Marine Science and Engineering, 2024, 12(1): 17.

[14] Wang Y, Zou T. Optimization of Berth-Tug Co-Scheduling in Container Terminals under Dual-Carbon Contexts[J]. Journal of Marine Science and Engineering, 2024, 12(4): 684.

[15] 卢翔, 张张, 李文豪. 纯电池动力系统在港作拖轮上的应用研究[J]. 船电技术, 2022, 42(8): 53-56.

LU X, ZHANG Z, LI W H. Study on the application of pure battery power system in craft tugs[J]. Marine electric & Electronic engineering, 2022, 42(8): 53-56. (in Chinese)

[16] 孙晓军, 宋恩哲, 姚崇. 船用混合动力推进系统能量管理系统关键技术研究现状[J]. 中国机械工程, 2022, 33(4): 469-481+495.

SUN X J, SONG E Z, YAO C. Research status of key technologies for energy management system of marine hybrid propulsion systems[J]. China Mechanical Engi-neering, 2022, 33(4): 469-481+495. (in Chinese)

[17] MIRJALILI S, LEWIS A. The Whale Optimization Algo-rithm[J]. Advances in Engineering Software, 2016, 95: 51-67.

[18] 闵德权, 张志铎, 张伟航. 基于港口环境效益的岸电与泊位联合分配优化研究[J]. 重庆交通大学学报（自然科学版）, 2023, 42(1): 83-90.

MIN D Q, ZHANG Z D, ZHANG W H. Optimization of joint allocation of shore power and berth based on envi-ronmental benefit of port[J]. Journal of Chongqing Jiao-tong University(Natural Science), 2023, 42(1): 83-90. (in Chinese)

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