Low-carbon economic scheduling of large ship power system based on multi-energy cooperative utilization

To mitigate costs and minimize environmental repercussions, integrated electric ship (IES) are an attractive option for developing greener, more efficient ships. Nevertheless, the service load uncertainty and the ineffective utilization of low-grade energy from diesel generators will hinder ships from attaining economical and low-carbon operation. Hence, an IES optimal joint scheduling model combining particle swarm optimization (PSO), waste heat recovery (WHR), and Latin hypercube sampling (LHS) is proposed. In this study, the mathematical modeling and reliability verification of the system are carried out, the performance of WHR is optimized, and the energy saving and emission reduction benefits of the combined system in IES's joint scheduling are explored. Simulation results illustrate that the innovative WHR integrated system can concurrently supply power, cooling capacity, and fresh water for IES, and the system yields 81.16 tons of fresh water during a single voyage. Finally, compared with Case 2, Case 1, which employs the transcritical CO 2 Rankine cycle and combined cooling and power system , reduces operating costs and CO 2 emissions by 2.3 % and 3.86 %, respectively, providing that the strategy proposed is effective in the IES's joint scheduling. • A new energy recovery system is proposed to integrated electric ship joint scheduling. • The particle swarm algorithm is utilized to optimize the energy recovery system. • Latin hypercube sampling is applied to simulate uncertain scenes of service load. • The costs and CO 2 emissions of integrated electric ship decrease by 2.3 % and 3.86 %.