海上交通动力消耗建模系统

H. A. Tvete, B. Guo, Qin Liang, H. Brinks
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引用次数: 4

摘要

国际海事组织(IMO)出于对环境和气候的担忧,对温室气体(GHG)的排放实施了更严格的限制。减少航运温室气体排放的措施可以分为两类。一是通过新技术、优化运营和物流来提高船舶能源效率;二是引入碳强度更低的替代燃料。然而,任何措施的有效性和适用性取决于船型、船舶尺寸、作业类型、作业环境(风浪条件)以及措施的成本。在实际航运场景中对新措施进行评估是必要的。船舶燃料消耗和排放模型是评估船舶对环境和气候影响以及评估减少温室气体排放的新措施的基础。基于船舶流体动力学模型、自动识别系统(AIS)信息、IHS Fairplay数据库和海洋气象数据,开发了一个船舶油耗和排放估算模型系统。该建模系统旨在覆盖配备AIS应答器的大多数船型,并将提供不同的流体动力学模型,根据可用的船舶信息计算燃料消耗。本文将对建模系统进行描述,并将建模系统的功耗与一艘集装箱船的测量数据进行比较。仿真结果表明,该模型预测的电耗与实测数据吻合较好。分析了气象数据和实测速度对预测电耗的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Modelling System for Power Consumption of Marine Traffic
The International Maritime Organization (IMO) has enforced stricter limit on the Greenhouse Gas (GHG) emission due to environment and climate concern. The measures to reduce GHG emissions from shipping can be divided into two groups. The first one is to improve ship energy efficiency through new technology, optimized operation and logistics, and the second one is to introduce alternative fuels with lower carbon intensity. However, the effectiveness and applicability of any measure depend on ship type, ship size, operation type, operation environment (wind and wave condition), as well as the cost of the measure. It is necessary to evaluate new measures in real shipping scenario. Modeling of ship fuel consumption and emission are fundamental input to evaluate the impacts of shipping on the environment and climate, and to evaluate new measures for reducing GHG emission. A modeling system is developed to estimate ship fuel consumption and emission, based on ship hydrodynamical models, information from Automatic Identification System (AIS), the IHS Fairplay database and metocean data. The modeling system aims to cover most of the ship types equipped with AIS transponders, and it will provide different hydrodynamical models to calculate fuel consumption based on the available ship information. In the paper, the modeling system will be described, and the power consumption from the modeling system are compared with the measurement data on one container ship. The comparison shows that the power consumption predicted with the modeling system agrees with measurement data well. The effects of weather data and measured speed on predicted power consumption are also analyzed.
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