Robust coordinated scheduling for multiple port-integrated energy systems using mobile energy storage vessels under source-load uncertainty

The unique geographical locations of ports endow them with abundant renewable energy resources. Energy cooperation among multiple ports can enhance the overall utilization of renewable energy and improve economic efficiency. To facilitate such collaboration, mobile energy storage vessels (MESVs) can be employed to achieve energy sharing and complementarity among the ports. Building upon research on mobile energy storage in multi-microgrid systems, this paper proposes a three-layer scheduling optimization framework for multiple port-integrated energy systems (PIESs) under source-load uncertainty. Firstly, a two-stage robust optimization model is established for each PIES to handle fluctuations in renewable energy generation and load, aiming to minimize operating costs under the worst-case scenario. Secondly, a novel integration of the two-stage robust optimization model and the analytical target cascading method is developed, which forms a three-layer optimization architecture. The upper layer manages the internal energy scheduling of each PIES, the middle layer coordinates energy interactions among multiple PIESs, and the lower layer allocates energy transportation tasks to the MESVs. Furthermore, a profit distribution mechanism based on the asymmetric Nash bargaining model is introduced to equitably quantify the contributions of all participants. Finally, simulation results demonstrate the effectiveness and advantages of the proposed framework.