Multi-Objective Multistage Distributionally Robust Flexibility Enhancement for Seaport Logistic-Energy Coordination

Logistic-energy coordination is an effective way to improve energy efficiency for electrified seaports. However, exiting works adopt fixed logistic power load models and seldom address renewable energy uncertainty adequately, resulting in low system flexibility and robustness. In this paper, a novel logistic-energy collaborative dispatch model is first proposed. The model integrates energy feedback from all-electric ships (AESs) and electric-powered cranes as well as automated guided vehicles (AGVs) battery swapping mode into entire logistic-energy coordination process. Logistic-side flexibility provision is significantly enhanced by variable bidirectional power flows and win-win battery swapping. Then a multi-objective multistage distributionally robust optimization (MMDRO) framework is established to address renewable energy uncertainty. This enables a trade-off between multiple objectives while ensuring solution non-anticipativity, economics and robustness via multistage distributionally robust optimization (DRO). The MMDRO is intractable due to multi-objectives, mixed-integer property and nested min-max-min optimization structure. To this end, an improved multi-objective stochastic dual dynamic integer programming (SDDiP) algorithm with controllable convergence process and two-step weight update is developed to effectively solve the model. Case studies demonstrate the superiority of our approach over existing methods.