航速优化是船舶智能能效管理的主要组成部分，对降低船舶营运成本、减少温室气体排放具有重要意义。为减少船舶航行时的主机燃油消耗，根据实船数据首先构建了主机油耗模型，模型的平均误差仅为0.813%，然后对整个航程进行分段，基于人工蜂群算法对整个航程的航速进行优化。经过验证可得结论：优化后的航速对应的整个航程航行时间减少了14.44%，油耗量降低了3.012%。研究结果表明，使用人工蜂群算法对航速进行优化，能够对航速提出建议，达到提高船舶能效水平，提高经济性、环保性的目标。
Speed optimization is an important part of ship intelligent energy efficiency management, which is of great significance to reduce ship operating costs and reduce greenhouse gas emissions. In order to reduce the main engine fuel consumption during ship navigation, the main engine fuel consumption model is constructed according to the real ship data, and the average error of the model is only 0.813%. Then the whole voyage is segmented, and the speed of the whole voyage is optimized based on artificial bee colony algorithm. After verification, it can be concluded that the whole voyage time corresponding to the optimized speed is reduced by 14.44%, and the fuel consumption is reduced by 3.012%. The results show that the use of artificial bee colony algorithm to optimize the speed can make recommendations to improve the energy efficiency of ships ; improve economic, environmental goals.
2023,45(19): 64-69 收稿日期：2022-07-25
DOI：10.3404/j.issn.1672-7649.2023.19.012
分类号：U676.3
作者简介：郭霆(1975-),男,硕士,副教授,研究方向为船舶自动化
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