A multi-objective optimisation framework for the design of ship energy systems under operational and environmental uncertainty - Vasilikis, Nikolaos; Geertsma, Rinze; Coraddu, Andrea (Applied energy, 2025)
Hybrid propulsion is considered a reliable alternative to solely mechanical or electrical propulsion for enhanced ship energy performance. Nevertheless, an increased number of components and interconnections results in more complex ship design problems. The automotive and aviation industries already examine new designs on predefined driving and flying cycles. However, new ships are still assessed on one design point with the regulated Energy Efficiency Design Index (EEDI). Its limited consideration of calm water conditions and installed rated power is characterised as insufficient, if not dangerous. A design methodology that accounts for operational and environmental uncertainty is lacking. This paper proposes a design optimisation framework for the topology selection and sizing of hybrid propulsion systems integrating probability distributions of actual sailing profiles from continuous monitoring. The methodology is demonstrated on the ‘Holland’ class ocean patrol vessels of the Royal Netherlands Navy. Its multi-objective consideration examines a wide design space from an environmental, financial, and technical perspective, solving the mixed-integer nonlinear programming (MINLP) problem with a multi-starting scheme that combines a genetic algorithm and interior point method. The low computational cost is achieved by integrating a state-of-the-art digital twin approach leveraging data-driven and first-principle modelling. The results demonstrate feasible improvements of approximately 4 % for carbon intensity and 11 % for operational expenditure by increasing the size of the electrical motors. The exact configuration and percentage improvement are sensitive to actual operational and environmental conditions, while calm water conditions tend to overestimate savings. Consequently, the use of actual sailing profiles is recommended for more accurate life-cycle predictions. •Use of discretised probability distributions of actual sailing profiles of sister ships.•A framework that considers environmental, financial and technical objectives.•A modelling approach that allows for extensive design space exploration.•A solver combining a genetic algorithm and interior point method in a multi-start scheme.•Calm water and typical design assumptions misleading in life-cycle assessments.