The ship’s power system is one of the most important systems on board. It is designed for uninterrupted power supply to all ship consumers under different conditions of exploitation. When designing a ship, various optimizations are conducted to build the ship as economically and environmentally friendly as possible. The paper aims to analyze the possibility of applying renewable energy sources (RES), particularly solar and wind energy, on an existing vessel by conducting technical and economic analysis. Data for the solar hour’s number and wind distribution are gathered from the six locations in the Adriatic Sea over 32 years period. Firstly, it was investigated if data were position dependent or independent. Performing a Pearson correlation coefficient and an ANOVA analysis with F-test, it was concluded that the RES analysis is position-independent (p > 0.05, p = 0.826). Secondly, the energy system model created in Simulink was used for the analysis of the electrical network fundamental parameters. Finally, the object of the analysis is the total costs of procurement, installation, and maintenance of the system within a period of 25 years. Consequences are savings in the cost of exploitation and reduction of harmful gas emissions. The use of solar energy would result in savings of 111,556 L of diesel fuel, while the savings from wind energy would be 170,274 L of diesel fuel for 25 years.

Decarbonization of shipping is a legal obligation imposed by the International Maritime Organization (IMO). The ferry port and daily operations located near or in urban zones negatively impact the nearby environment. The electrification of ferries contributes to reducing the negative environmental impact. The available electrical infrastructure in ports often does not meet daily needs. The ferry fleet’s sailing schedule creates a non-periodic daily energy profile to determine the energy needs of the shore connection. The proposed research aims to optimize the daily electric ferry fleet peak charging power schedule process using particle swarm optimization and a greedy algorithm. A four-stage model has been proposed, consisting of the initialization of the ferry fleet’s daily energy profile, initial population generation with input constraints, optimization, and the creation of the modified daily energy load diagram. Robustness and validation of the proposed model were investigated and proven for energy profiles with and without optimization. For the proposed charging schedule, the study results show a reduction in peak power of 24%. By optimizing the charging process, peak charging power has been reduced without needing an additional energy storage system.

Maritime transportation significantly contributes to air pollution, especially in coastal cities. Air pollution represents the greatest health risk related to the environment in the European Union. Therefore, the European Commission published the European Green Deal, which introduces the rule of zero-emission requirements for ships at berths with the mandatory use of power supply from shore or alternative technologies without emissions. The electrification of ferries has proven to be a key approach in reducing the negative impact on the environment; hence, it is necessary to provide adequate infrastructure for charging electric ferries. To determine the energy needs of the shore connection, a daily energy profile of the ferry fleet was created. Due to the sailing schedule, daily energy needs may be non-periodic. By optimizing the charging process, a reduction in peak charging power can be achieved. The charging process was optimized using particle swarm optimization. To improve the function goal, the parameters of the model were analyzed and optimized. It was found that the correct selection of population size and inertia weight factor can significantly enhance the optimization effect. The proposed model can be applied to other ports of interest, considering the specifics of the exploitation of the fleet of ships.

The International Maritime Organization (IMO) is introducing increasingly strict controls in several aspects of maritime transport with the aim of preserving the environment. Various technologies are proposed and applied that reduce the emission of greenhouse gases. One of the approaches is the application of renewable energy sources RES. However, RES are not equally suitable for all types of ships sailing in different geographical areas. The flow diagram in the process of making a decision on the selection of the type of RES is proposed. This paper presents a model for selecting the most suitable RES on vessels. Furthermore, the optimal solution is selected using Bayesian networks. All significant parameters that influence the selection of the optimal solution can be taken into account and are elaborated individually.