Probabilistic Coordination of Optimal Power Management and Voyage Scheduling for All-Electric Ships

To improve energy utilization, the use of solar power into an all-electric ship (AES) has drawn more attention. Furthermore, as fully electrified propulsion technology has been introduced into shipboard microgrids, more extensive electrification of ships to make AESs has become an appealing solution to increase efficiency and environmental friendliness. However, a range of uncertainties that are associated with renewable energy, waves, and ship motions significantly deteriorate and complicate the operation and navigation of ships. To reduce simultaneously the operating cost and greenhouse gas emissions, a stochastic coordination framework is proposed in this article to optimize jointly the power management and voyage scheduling. In regard of various uncertainties, a new comprehensive day-ahead probabilistic scheduling algorithm is developed in this article for a photovoltaic penetrated AES, which combines Taguchi's orthogonal method with adaptive multiobjective particle swarm optimization. Different cases are considered and compared to verify the effectiveness of the proposed method for a cruise ship. Simulation results clearly reveal that the proposed hybrid optimization algorithm can improve environmental friendliness and on-board energy efficiency, while accommodating diverse uncertainties.