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There is an environmentally and economically motivated need to reduce the fuel consumption and air emissions of ships. To achieve a reduction in energy consumption, the energy flow in the entire energy system of a ship must be analysed in both the component, or subsystem, level as well as in a holistic way to capture the interactions between the components. Of the currently available energy consumption monitoring and prediction methods or models, no single model or method can be used to assess the energy efficiency of an arbitrary vessel in both the early design phase and during operation. This study presents a new generic ship energy systems model that can be used for this purpose. This new model has two parts: one for the assessment of a ship's energy consumption based on an ordinary static power prediction and one for advanced operational analysis, considering hydrodynamic and machinery systems effects. A Panamax tanker vessel was used as the case study vessel to prove the versatility of the model for five example simulations for the design and operation of ships. The examples include variations of the main dimensions, propeller design, engine layout and the operational profile on a North Atlantic route. From the results, different areas with a potential for energy savings were identified.

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As increasing numbers of merchant ships navigate in the Arctic waters, more energy efficient 10 navigation in the Arctic is needed for both economic and environmental purposes. This paper aims to 11 provide a comprehensive analysis of energy efficiency of ice-going ships. Firstly, a data-driven model based 12 on neural network theory is developed to predict the energy efficiency of ships in the Arctic. Then, a route 13 with optimum energy efficiency is presented, intended to cut costs and be as environmentally friendly as 14 possible. Finally, a case study is carried out to analyze the performance of a case study ship sailing at 15 various environmental conditions. The results indicate that when planning the route for such an Arctic ship, 16 it would be shortsighted only to focus on distance rather than energy efficiency. Moreover, the model shows 17 good agreement between the simulation and real-life navigation. It is expected that the construction of this 18 multi-angle, energy efficiency optimization model could help to improve Arctic navigation.19

This investigation presents an approach towards a better understanding of achievable accuracy of fuel consumption predictions of ships and provides an example of how a thorough uncertainty analysis of prediction models can be performed. A generic ship energy systems model is used for the fuel consumption prediction of two reference ships: a RoRo ship and a tanker. The study presents how uncertainties can be categorised and handled in four different phases of a ship's life -from early design to ship operation. Monte Carlo simulations are carried out for two environmental conditions to calculate the mean and uncertainty of the fuel consumption. The results show that the uncertainty in the fuel consumption prediction in a very early phase of the design process is approximately 12%, whereas at a very late phase, it reduces to less than 4%. Finally, the simulation model is applied to a real ship during operation conditions.