基于PSO的燃料电池船舶航速与功率分配策略协同优化

PSO-based speed and power allocation strategy collaborative optimization method for hydrogen fuel cell ships

  • 摘要:
    目的 针对复杂航行环境下难以获取最优航速而导致燃料电池船舶的能效提升有限的问题,提出基于粒子群算法的燃料电池船舶航速与功率分配策略协同优化方法。
    方法 采用K-means对气象环境数据进行空间网格聚类分析并作为航线分段的依据,进而通过船舶航行阻力分析和等效氢耗思想构建燃料电池船舶的航速–氢耗模型。同时,以加速度为优化参数设计航速优化值在航段之间传承–链接的优化方式,进而运用粒子群算法对船舶全航程航速和燃料电池输出功率进行优化。
    结果 仿真验证结果表明,相较于原航速和传统航速分段优化方法,航速与功率分配策略协同优化方法分别降低了3.85%和1.99%的氢气消耗。
    结论 该方法有效提高了短程船舶航行能效,并改善了传统分段优化的航速阶梯分布缺陷问题,可为燃料电池船舶的推广应用提供参考。

     

    Abstract:
    Objectives This paper proposes a speed and power allocation strategy collaborative optimization method for hydrogen fuel cell ships based on particle swarm optimization (PSO) in order to solve the problem of the energy efficiency improvement of such ships being limited by their difficulty in reaching optimal speed under complex sailing environments.
    Methods The spatial grid clustering analysis of meteorological environment data is carried out by K-means and used as the basis for route segmentation. A speed-hydrogen consumption model of a fuel cell ship is constructed by ship navigation resistance analysis and the equivalent hydrogen consumption idea. The optimization method of inheritance-link between voyage segments is designed by taking acceleration as the optimization parameter, then PSO is used to optimize the ship's speed and fuel cell output power.
    Results The results show that the proposed speed and power allocation strategy collaborative optimization method reduces hydrogen consumption by 3.85% and 1.99% respectively compared with the original speed and traditional speed segmentation optimization method.
    Conclusions The proposed method can effectively improve the sailing energy efficiency of short-range ships and resolve the defect of the speed ladder allocation of traditional segmental optimization, providing useful references for the popularization and application of hydrogen fuel cell ships.

     

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