Predicting route-specific energy demand under realistic environmental behaviour

To meet current and forthcoming international regulations, it is essential to reduce emissions and increase the efficiency of ships. A prevailing approach is to install hybrid drive systems to optimize the engine load. Evaluating the actual efficiency gains of a battery-supported ship compared to a conventional system requires detailed knowledge of its operational proőle. Battery support proves advantageous primarily in applications with highly variable power demands. However, the data basis is often limited to statistical power distributions rather than continuous data. Since the state of charge of the battery is time-dependent, a continuous time series of the power demand is crucial for accurate sizing of system components. Additionally, the operational proőle is inŕuenced by environmental factors that vary statistically and regionally. To capture realistic power demand patterns, the environmental forces must also be incorporated in time domain. Therefore, this paper presents a manoeuvering simulation for predicting power demand along a ship route under realistically changing environmental conditions. The calculations utilize a fast, in-house, force-based manoeuvering approach that accounts for environmental factors such as seaway, wind, currents, and shallow water effects. Arbitrary ship routes are deőned by waypoints on a map, which are automatically navigated using the line-of-sight concept. Environmental data is sourced from the ERA5 database, providing information at speciőc geographical grid points. A spatial and temporal interpolation process generates a realistic continuous proőle of these ambient parameters based on the ship’s current position along its route. The simulated results align strongly with measured data, conőrming the model’s validity.

Subjects

Battery Support

Manoeuvring Simulation

Operational Profile

Ship Design

Ship Efficiency

DDC Class

600: Technology

Options

Predicting route-specific energy demand under realistic environmental behaviour