The maritime industry is under increasing pressure to reduce its greenhouse gas (GHG) emissions. European ports, including the Port of Rotterdam, are transitioning to sustainable solutions to reduce their environmental impact. Since the Port of Rotterdam is large, patrol and incident-response (RPA) vessels are needed to ensure a safe port. However, the existing fleet is reaching its operational end of life. These vessels currently rely on conventional propulsion systems, which are not in line with the sustainability goals of the Port of Rotterdam. The Port of Rotterdam performed research with several companies to see what type of renewable energy solutions could be applied to the new RPA vessels. Given the 24/7 operational profile and energy demands of (relatively small) RPA vessels, a battery or hydrogen propulsion system installed onboard the vessels was not an option. Therefore, another possibility was proposed: the (rapid) swapping of energy modules to and from the vessel at swapping stations.

This research addresses the challenge of designing an optimal configuration for such a swapping method based on the operational sailing profiles of RPA vessels. A systematic methodology was applied, starting with a literature review for the technical and operational issues. The findings highlighted the feasibility of implementing a Battery Energy Storage System (BESS) powered by lithium-ion batteries, supported by decentralised swapping and charging stations structure. Different concepts for the Battery Swapping Method (BSM) were considered from which the Shfitr concept was the most promising application for this thesis. The Shiftr concept uses cranes to automatically swap energy modules to and from vessels. Different optimisation methods were investigated to see which one best supports finding an optimal configuration (energy modules, swapping/charging stations and vehicle related). It was concluded that a Mixed Integer Linear Programming method could be best applied, with the objective to minimise downtime of the swapping process for different configurations.

A mathematical model for the optimisation model was developed to minimise downtime during swapping, incorporating historical AIS data to simulate the vessels’ operational profiles. This optimisation model can track both the vessel r and the modules m for each time t. This mathematical model is made in Gurobi (Python) and can, for different configurations, minimise the total swapping time for a given period of data. The configurations are used as input data, including the number of energy modules and the number/placement of swapping and charging stations based on the energy consumption of vessels and their sailing path defined during the pre-processing. Verification and validation confirmed the optimisation model was working, although computational challenges were observed when validating each individual vessel.

After verification and validation, two case studies were performed, which included multiple vessels. Due to the rapid increase in computational time, only two case studies were performed with two and three vessels, respectively. Except for the number of vessels, the configuration from the pre-processing was the same for both the case studies. For both cases, the number of swaps was in line with the expectations of each case and confirmed the working of the optimisation model. As the vessels only lost minutes on swapping while sailing for hours before the modules were depleted, a low swapping frequency was observed in the optimisation model. At the same time, there are too many swapping stations in the configuration, leading to a lot of unused energy modules.

In conclusion, the optimisation model can successfully optimise the sailing path to minimise swapping time, for a specific configuration. However, the research question of finding the optimal configuration could not be answered fully. Therefore, further research is needed to address computational limitations and to optimise module utilisation. This thesis provides a foundation for swapping renewable energy sources in modules, for relatively small vessels, which are operational 24/7.