| Summary: | In order to reduce greenhouse gas emissions (GHG) from ships at sea, various measures have been considered, such as alternative fuels with low carbon intensity, innovative ship technology, and new policies. To successfully achieve GHG reduction in global shipping, it is critical to properly evaluate and understand the impact of the combination of operational scenarios and various mitigation measures, which requires a system that can accurately predict the required power for the global fleet under the actual operating profile and weather conditions. Global emissions assessments in the maritime sector have relied on relatively simplified calculations and empirical methods to estimate power consumption due to limitations such as a lack of accurate information about ships, uncertainty in the collected data, and computational complexity. This study aims to implement an improved model that can improve the accuracy of power predictions by identifying suitable methods for fleet-wide power estimation or modifying and updating existing methods. Based on the developed model, the application and effectiveness of energy saving measures are also considered. An overall data processing method for performance analysis of individual ships and entire fleet segments, including a method for processing missing values of ship principal parameters, is presented. In addition, methods for estimating ship resistance components and total propulsive efficiency are reviewed. Here, a new method for estimating added wave resistance of a ship is developed. Moreover, air lubrication technology is combined with the developed power prediction model as a case study for energy saving measures, and its impact on energy savings in global shipping is evaluated. Based on the comparison results with the full-scale measurements and 2018 EUMRV (European Union-The Monitoring, Reporting and Verification) data, the developed model seems to well describe the characteristics of the power performance according to the ship’s various operational profiles. It can ...
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