Integrated-energy ship-power optimization scheduling considering the uncertainty of photovoltaic output

Abstract As air pollution increases and the energy crisis intensifies, marine renewable energy technologies have rapidly become crucial. Compared with traditional ships, the integrated onboard energy microgrid system enables pollution-free, renewable, and efficient energy utilization. However, the integration of electricity, hydrogen, and heat within an integrated-energy shipborne microgrid system presents challenges to existing optimization methods. Therefore, given that traditional ship energy models struggle to effectively handle the uncertainty of photovoltaic output, this paper proposes a novel two-level optimization framework based on the multi-objective artificial hummingbird algorithm to achieve multi-energy collaborative scheduling. This model integrates diesel generators, hydrogen fuel cells, photovoltaic systems, energy storage systems (ESSs), and heat storage devices, and it responds to spatiotemporal fluctuations in the marine environment through an electric-hydrogen-thermal coupling mechanism. The upper-level model achieves the optimal scheduling of power generation equipment and loads, and the lower-level optimization model is established to reduce the lifetime loss of an ESS. An improved multi-objective artificial hummingbird algorithm is introduced to obtain the optimal scheduling solution of the two-level optimization scheduling model. Simulation results demonstrate that the proposed optimization method not only reduces greenhouse gas emissions by 44.6% but also increases the cycle life of the ESS by 8.06%.