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智能船舶综合能源系统及其分布式优化调度方法

滕菲 单麒赫 李铁山

滕菲, 单麒赫, 李铁山. 智能船舶综合能源系统及其分布式优化调度方法. 自动化学报, 2020, 46(9): 1809−1817 doi: 10.16383/j.aas.c200176
引用本文: 滕菲, 单麒赫, 李铁山. 智能船舶综合能源系统及其分布式优化调度方法. 自动化学报, 2020, 46(9): 1809−1817 doi: 10.16383/j.aas.c200176
Teng Fei, Shan Qi-He, Li Tie-Shan. Intelligent ship integrated energy system and its distributed optimal scheduling algorithm. Acta Automatica Sinica, 2020, 46(9): 1809−1817 doi: 10.16383/j.aas.c200176
Citation: Teng Fei, Shan Qi-He, Li Tie-Shan. Intelligent ship integrated energy system and its distributed optimal scheduling algorithm. Acta Automatica Sinica, 2020, 46(9): 1809−1817 doi: 10.16383/j.aas.c200176

智能船舶综合能源系统及其分布式优化调度方法

doi: 10.16383/j.aas.c200176
基金项目: 国家自然科学基金(61803064), 中央高校基本科研业务费专项资金(3132020103, 3132020125)资助
详细信息
    作者简介:

    滕菲:大连海事大学船舶电气工程学院讲师. 主要研究方向为分布式优化技术及其在综合能源系统领域相关应用.E-mail: brenda_teng@163.com

    单麒赫:大连海事大学航海学院副教授. 主要研究方向为多智能体控制, 分布式优化, 船舶能耗优化. 本文通信作者.E-mail: shanqihe@dlmu.edu.cn

    李铁山:电子科技大学自动化工程学院教授. 主要研究方向为智能船舶控制理论与技术, 非线性系统智能控制理论与应用研究.E-mail: litieshan073@uestc.edu.cn

Intelligent Ship Integrated Energy System and Its Distributed Optimal Scheduling Algorithm

Funds: Supported by National Natural Science Foundation of China (61803064), the Fundamental Research Funds for the Central Universities (3132020103, 3132020125)
  • 摘要: 船舶航运污染是阻碍海洋经济发展、海洋强国建设的瓶颈问题. 智能船舶为航运业绿色环保发展提供了重要手段. 为进一步开发船载新能源, 提升能源综合利用效率, 降低船舶航运污染排放, 本文构建以能量优化调度系统为核心、以能源转换中心为枢纽的智能船舶综合能源系统; 考虑其特有的动力系统负荷需求、航行低污染排放量标准以及电−热多能流耦合供能特性, 建立智能船舶综合能源系统能量优化调度目标函数及相关约束条件; 并基于宽度学习、带有广义噪声的多智能体分布式优化相关理论, 提出可快速准确地预测全航程各时段负荷需求、可容纳复杂干扰的分布式优化调度方法, 实现高效的智能船舶综合能源系统能量优化调度, 保障智能船舶经济、可靠、稳定航行. 仿真分析验证了所提出智能船舶综合能源系统分布式优化调度方法的有效性.
  • 图  1  智能船舶综合能源系统基本结构框图

    Fig.  1  The typical architecture of intelligent ship integrated energy system

    图  2  智能船舶综合能源系统仿真模型

    Fig.  2  The simulation model of intelligent ship integrated energy system

    图  3  智能船舶综合能源系统全航程分布式优化调度考虑的广义噪声干扰

    Fig.  3  The general noise considered in the distributed optimal scheduling during the whole voyage of intelligent ship integrated energy system

    图  4  船舶航行$6\sim 10 $小时时段各供能设备电输出功率

    Fig.  4  Electricity output of each energy supply equipment during $6\sim 10 $ hours sailing

    图  5  船舶航行$6\sim 10 $小时时段各供能设备热输出功率

    Fig.  5  Heat output of each energy supply equipment during $6\sim 10 $ hours sailing

    图  6  智能船舶航行航线全航程各时段各供能设备最优电输出功率

    Fig.  6  The optimal electricity output of each energy supply equipment of intelligent ship in different periods of the whole voyage

    图  7  智能船舶航行航线全航程各时段各供能设备最优热输出功率

    Fig.  7  The optimal heat output of each energy supply equipment of intelligent ship in different periods of the whole voyage

    表  1  智能船舶全航程各时段电−热负荷预测结果

    Table  1  The forecast results of electric and thermal load of intelligent ship in different periods of the whole voyage

    全航程各时段热
    负荷预测量 (MW)
    1小时2小时3小时4小时5小时6小时7小时8小时9小时10小时11小时12小时
    19.000028.988933.000034.000032.000027.000020.000016.000018.000027.978033.000034.0000
    13小时14小时15小时16小时17小时18小时19小时20小时21小时22小时23小时24小时
    36.000029.000020.000016.000019.000029.967130.000035.000031.000028.000019.495718.0000
    全航程各时段电
    负荷预测量 (MW)
    1小时2小时3小时4小时5小时6小时7小时8小时9小时10小时11小时12小时
    29.360055.325561.610062.430060.830048.850033.730025.250032.160057.388561.080059.7900
    13小时14小时15小时16小时17小时18小时19小时20小时21小时22小时23小时24小时
    65.180055.480035.250026.600032.700054.362954.590064.240056.610054.930032.903928.2700
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-03-31
  • 录用日期:  2020-06-28
  • 网络出版日期:  2020-09-28
  • 刊出日期:  2020-09-28

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