Integrated optimization of speed schedule and energy management for a hybrid electric cruise ship considering environmental factors

Severe global energy crisis and greenhouse effect have promoted the rapid growth of hybrid electric propulsion systems (HEPSs) applied to cruise ships. However, the conventional methodologies, which optimize sailing speed and energy management separately, restrict the improvement of the ship energy efficiency. This study proposes an integrated optimization of speed schedule and energy management considering changes in wind, waves, and drifting ice during the voyage. First, a refined energy flow model of the HEPS against the resistance from wind, waves, and drifting ice in addition to the hydrostatic pressure is established. Second, the integrated optimization problem of speed schedule and energy management is formulated to pursue minimal fuel consumption. Third, the complex optimization problem is solved by a low computation load algorithm, in which the K-means algorithm and physical turning points divide the target route into several segments considering environmental characteristics, the particle swarm optimization algorithm optimizes the speed in each segment, and the equivalent fuel consumption minimization strategy optimizes the energy management during sailing. Finally, two case studies of a cruise ship sailing in the Drake Passage validate the effectiveness of the proposed method. The results show that the integrated optimization significantly reduces fuel consumption compared with the conventional separation optimization in terms of either speed schedule or energy management, as well as the conventional heuristic strategy. Furthermore, the integrated optimization demonstrates advantages in reducing greenhouse emissions caused by fuel and electricity consumption of the HEPS.