Electric Ferry Fleet Peak Charging Power Schedule Optimization Considering the Timetable and Daily Energy Profile

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.