A novel cooperative optimization method of course and speed for wing-diesel hybrid ship based on improved A* algorithm

被引:4
|
作者
Wang, Cong [1 ]
Huang, Lianzhong [1 ]
Ma, Ranqi [1 ]
Wang, Kai [1 ]
Sheng, Jinlu [2 ]
Ruan, Zhang [1 ]
Hua, Yu [1 ]
Zhang, Rui [1 ]
机构
[1] Dalian Maritime Univ, Marine Engn Coll, Dalian 116026, Liaoning, Peoples R China
[2] Chongqing Jiaotong Univ, Sch Shipping & Naval Architecture, Chongqing 400074, Peoples R China
基金
中国国家自然科学基金;
关键词
Wing-diesel hybrid ship; Variables normalization; Cooperative optimization; Improved a* algorithm; FUEL CONSUMPTION;
D O I
10.1016/j.oceaneng.2024.117669
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
The wing-diesel hybrid ship, utilizes a wind propulsion system, which is significantly influenced by weather conditions. Therefore, a cooperative optimization method for course and speed is proposed based on an improved A* algorithm, considering weather changes and the ship characteristics, to achieve further improvement in the ship operational energy efficiency. Firstly, a meteorological and hydrological dataset is utilized to establish a dynamic maritime area model with complex weather conditions. Based on this model, the paper considers the actual navigation circumstances to define prohibited and navigable areas. Secondly, the improved A* algorithm incorporates the impact of weather on wing-sails. The improved A* algorithm considers the ship operating position and enhances the evaluation function by variables normalization of fuel consumption and voyage time. This cooperative optimization ensures the maximization of wind energy utilization, thereby achieving the goal of reducing fuel consumption while meeting the overall voyage time requirement. Experimental validation is conducted with the ship "New Aden" in the Indian Ocean region, and the results show that, compared to the original route, the optimized route reduces total fuel consumption by 5.48%, increases the navigation distance by up to 2.18% and increases the navigation time by 5.74%.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] A novel prediction method of fuel consumption for wing-diesel hybrid vessels based on feature construction
    Ruan, Zhang
    Huang, Lianzhong
    Wang, Kai
    Ma, Ranqi
    Wang, Zhongyi
    Zhang, Rui
    Zhao, Haoyang
    Wang, Cong
    ENERGY, 2024, 286
  • [2] A novel method of fuel consumption prediction for wing-diesel hybrid ships based on high-dimensional feature selection and improved blending ensemble learning method
    Lan, Tian
    Huang, Lianzhong
    Ma, Ranqi
    Ruan, Zhang
    Ma, Shan
    Li, Zhongwei
    Zhao, Haoyang
    Wang, Cong
    Zhang, Rui
    Wang, Kai
    OCEAN ENGINEERING, 2024, 307
  • [3] Joint energy consumption optimization method for wing-diesel engine-powered hybrid ships towards a more energy-efficient shipping
    Wang, Kai
    Xue, Yu
    Xu, Hao
    Huang, Lianzhong
    Ma, Ranqi
    Zhang, Peng
    Jiang, Xiaoli
    Yuan, Yupeng
    Negenborn, Rudy R.
    Sun, Peiting
    ENERGY, 2022, 245
  • [4] Ship Cabin Layout Optimization Design Based On The Improved Genetic Algorithm Method
    Wang, Yun Long
    Wang, Chen
    Lin, Yan
    MECHATRONICS AND APPLIED MECHANICS II, PTS 1 AND 2, 2013, 300-301 : 146 - 149
  • [5] An energy dispatch optimization for hybrid power ship system based on improved genetic algorithm
    Wang, Xinyu
    Zhu, Hongyu
    Luo, Xiaoyuan
    Chang, Shaoping
    Guan, Xinping
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART A-JOURNAL OF POWER AND ENERGY, 2024, 238 (02) : 348 - 361
  • [6] A novel particle swarm and genetic algorithm hybrid method for diesel engine performance optimization
    Bertram, Aaron M.
    Zhang, Qiang
    Kong, Song-Charng
    INTERNATIONAL JOURNAL OF ENGINE RESEARCH, 2016, 17 (07) : 732 - 747
  • [7] A Novel Hybrid Model Based on an Improved Seagull Optimization Algorithm for Short-Term Wind Speed Forecasting
    Chen, Xin
    Li, Yuanlu
    Zhang, Yingchao
    Ye, Xiaoling
    Xiong, Xiong
    Zhang, Fanghong
    PROCESSES, 2021, 9 (02) : 1 - 21
  • [8] A Collision Avoidance Method for Intelligent Ship Based on the Improved Bacterial Foraging Optimization Algorithm
    Wang, Xingzhong
    Kou, Xinghua
    Huang, Jinfeng
    Tan, Xianchun
    JOURNAL OF ROBOTICS, 2021, 2021
  • [9] Intelligent Layout Method of Ship Pipelines Based on an Improved Grey Wolf Optimization Algorithm
    Lu, Yongjin
    Li, Kai
    Lin, Rui
    Wang, Yunlong
    Han, Hairong
    JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2024, 12 (11)
  • [10] Research on wind speed forecasting method based on hybrid Copula optimization algorithm
    Huang Y.
    Zhang B.
    Pang H.
    Xu J.
    Liu L.
    Wang B.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2022, 43 (10): : 192 - 201