Optimizing ship energy efficiency: Application of particle swarm optimization algorithm

被引:28
|
作者
Wang, Kai [1 ,2 ,3 ]
Yan, Xinping [1 ,2 ,3 ]
Yuan, Yupeng [1 ,2 ,3 ]
Tang, Daogui [1 ,2 ,3 ]
机构
[1] Wuhan Univ Technol, Sch Energy & Power Engn, Reliabil Engn Inst, Wuhan 430063, Hubei, Peoples R China
[2] Wuhan Univ Technol, Minist Transport, Key Lab Marine Power Engn & Technol, Wuhan, Hubei, Peoples R China
[3] Wuhan Univ Technol, Natl Engn Res Ctr Water Transport Safety, Wuhan, Hubei, Peoples R China
关键词
Greenhouse gas emission; energy saving and emission reduction; EEOI; energy efficiency management; multi-objective optimization; particle swarm optimization; SYSTEM; LNG;
D O I
10.1177/1475090216638879
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
Greenhouse gas emission and subsequent global warming have attracted more and more attention all over the world. As one of the biggest emission sources, shipping industry is suffering great emission reduction pressure from the public. Although shipping industry can improve the energy efficiency by exploring new strategies to reduce the fuel cost and the emission to air, some deficiencies may be discovered in practice due to lack of a comprehensive consideration of other significant factors, such as safety factors. Therefore, energy efficiency management strategies that consider both safety and economy factors have more practical significance for enhancing the ship energy efficiency. In this article, a power supply model considering economy, emission reduction and safety was established, and a multi-objective optimization problem to keep the system working at a high safety level, a low CO2 emission and a moderate fuel consumption was proposed. Furthermore, the particle swarm optimization algorithm was adopted to solve the multi-objective optimization problem, and the obtained non-inferior solutions could help officers on duty to select the optimum main engine speed by weighing the economy and the safety of the ship. The results show that the proposed method of energy efficiency management could reduce the greenhouse gas emission and the energy efficiency operation index (EEOI) of the ship effectively. The trade-off between ship economy, emission and robustness of the power supply system was studied, which is meaningful to the energy efficiency improvement and the CO2 emission reduction under the safety requirement of power supply.
引用
收藏
页码:379 / 391
页数:13
相关论文
共 50 条
  • [21] Ship Heading Control Based on Improved Particle Swarm Optimization Algorithm
    Liang, Hao
    Wang, Huaming
    Fan, Lingmei
    Wang, Xinshuai
    Chen, Xiaoyu
    PROCEEDINGS OF THE WORLD CONFERENCE ON INTELLIGENT AND 3-D TECHNOLOGIES, WCI3DT 2022, 2023, 323 : 233 - 241
  • [22] An application of particle swarm optimization algorithm to clustering analysis
    Kuo, R. J.
    Wang, M. J.
    Huang, T. W.
    SOFT COMPUTING, 2011, 15 (03) : 533 - 542
  • [23] Cultural Particle Swarm Optimization Algorithm and Its Application
    Zhou Wei
    Bu Yan-ping
    PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : 740 - 744
  • [24] Application of particle swarm optimization algorithm to reservoir operation
    Huang, Qiang
    Zhang, Hong-bo
    Chen, Xiao-nan
    Lv, Yu-jie
    ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 5, PROCEEDINGS, 2007, : 595 - +
  • [25] An application of particle swarm optimization algorithm to clustering analysis
    R. J. Kuo
    M. J. Wang
    T. W. Huang
    Soft Computing, 2011, 15 : 533 - 542
  • [26] Application of improved particle swarm optimization algorithm in TDOA
    Liang, Zhen-dong
    Yi, Wen-jun
    AIP ADVANCES, 2022, 12 (02)
  • [27] The Application of Particle Swarm Optimization Algorithm on Absorbent Materials
    Feng, Hongquan
    Wu, Bingheng
    Liu, Yuanyun
    Liao, Yi
    Gu, Hao
    Yu, Xing
    ADVANCED RESEARCH IN MATERIAL SCIENCE AND MECHANICAL ENGINEERING, PTS 1 AND 2, 2014, 446-447 : 1541 - +
  • [28] Improvement and Application of Fractional Particle Swarm Optimization Algorithm
    Li, Jing
    Zhao, Chunna
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 2022
  • [29] Simplex particle swarm optimization algorithm and its application
    Chen, Guo-Chu
    Yu, Jin-Shou
    Xitong Fangzhen Xuebao / Journal of System Simulation, 2006, 18 (04): : 862 - 865
  • [30] The Research and Application of Chaotic Particle Swarm Optimization Algorithm
    Hu, Qiongqiong
    Liu, Huizhen
    Niu, Chengshui
    Du, Meiyun
    Zhang, Yu-an
    Ge, Yong
    2017 13TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD), 2017, : 1058 - 1062