港口船舶尾气排放量及泊位调度优化研究

    Optimization of berth scheduling to control ship exhaust emissions in port

    • 摘要: 为加强绿色港口建设、降低港口污染排放水平,基于海量船舶自动识别系统(AIS)数据挖掘船舶运行规律并应用分布式运算获取港口船舶污染物典型排放量及分布特征。结果表明,两种主要污染气体SOx和NOx呈现相似的变化趋势且船舶排放的尾气大多集中在泊位以及主航道上。经相关性分析发现,船舶活动水平因子与船舶尾气排放量呈显著正相关关系,船舶的到达数量及在港口的作业时间影响着泊位区域的污染水平。最后,针对现有的港口船舶调度机制和港口基础条件,基于AnyLogic建立仿真模型对港口泊位配置数量进行优化,有效降低了港口船舶的尾气排放量,为绿色航运提供了一种新的方案参考。

       

      Abstract: The regular pattern of ship's operation is mined by processing massive AIS data records. Typical volume and distribution characteristics of the emission from ships in port are calculated through distributed computing. An Anylogic-based simulation model is built to find optimum berth schedule in terms of minimum emissions from ships in port. The findings are as follows: the main pollutants emitted from ships, SOx and NOx, change in similar way and mostly are concentrated at berthing area and main channel. Correlation analysis shows that the emission volume of exhaust gas is positively correlated with ship's activity level. The pollution level at berthing area is dependent on number of ships calling and their working hours.

       

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