Distributed Energy Management for Ship-Integrated Energy System With Velocity Scheduling Toward Lower Carbon Emission

The development of the shipping industry relies heavily on fuel consumption and generates substantial quantities of carbon emissions. The ship-integrated energy system (S-IES) enhances the coordination of renewable technologies and fuel-based generators, facilitating carbon emission reduction and making it a popular energy architecture for modern ships. S-IES’s energy management problem (EMP) plays a crucial role in enhancing energy utilization efficiency and has been extensively investigated worldwide. However, the ships perform “port-to-port navigation” features, which are not considered in the EMP analysis for the ships. To this end, this paper focuses on the EMP of S-IES through a collaborative analysis of ships and ports, ensuring secure and stable navigation. This paper divides the energy management for S-IES into day-ahead scheduling and on-voyage scheduling. Firstly, an onshore electricity price prediction algorithm is developed utilizing ensemble learning theory to accurately forecast the port’s electricity price trends in the day-ahead scheduling. Secondly, a navigation voyage planning model optimizes the velocity plan, minimizing sailing duration and charging costs. Thirdly, a carbon trading mechanism is proposed in the on-voyage scheduling. Then, an energy dispatch issue concerning both carbon emission intensity and operation cost for the ships is constructed. Fourthly, a distributed algorithm is proposed to compute the energy dispatch solution, which can tolerate the disturbance influence brought by the information exchange among energy participants. Finally, sailing route data from the Queensland port to the Victoria port for “YUKUN” are adopted for the case studies. Simulation results prove the effectiveness of the proposed energy management strategy for the S-IES.