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 article, 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 the entire logistic-energy coordination process. Logistic-side flexibility provision is significantly enhanced by variable bidirectional power flows and win-win battery swapping. Then, a multiobjective multistage distributionally robust optimization (MMDRO) framework is established to address renewable energy uncertainty. This enables a tradeoff between multiple objectives while ensuring solution nonanticipativity, economics, and robustness via multistage distributionally robust optimization (DRO). The MMDRO is intractable due to multiobjectives, mixed-integer property, and nested min-max–min optimization structure. To this end, an improved multiobjective 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.
Multiobjective Multistage Distributionally Robust Flexibility Enhancement for Seaport Logistic-Energy Coordination
IEEE Transactions on Transportation Electrification ; 11 , 1 ; 693-709
01.02.2025
1667193 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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