Power allocation influence on energy consumption of a double-ended ferry

Paper i proceeding, 2023

Fuel is one of the highest cost items while operating a ship, and its combustion results in air emissions polluting environments. Finding ways to increase shipping operations efficiency without compromising the provided service quality is necessary for economic and environmental reasons. This study first used data analysis to find hidden information in one-year navigation data of a double-ended ferry operated along the Swedish coast. The case study ferry was operated using both bow and stern engines partly loaded. A new feature of the power ratio is defined to describe the influence of engine power allocation on total fuel consumption. Then, different machine learning methods are used to establish the ship’s total fuel consumption model due to influences of external factors such as wind and sea currents, etc., together with the power ratio. The established machine learning model is used to find the most efficient operation of allocating power to different engines. It shows that, in theory, up to 35% fuel savings can be achieved for the case study vessel. These findings can further aid with the operational planning for the scope of Eco-driving.