Sustainable electrified seaports: A coordinated energy and logistics scheduling approach for future maritime hubs

Coordinated logistics and energy scheduling deliver significant techno-economic benefits by optimizing energy usage, reducing operational costs, and enhancing efficiency in electrified seaports, driving sustainable and cost-effective port electrification. However, existing efforts focus on either logistics or energy system scheduling, overlooking the coupled operation dynamics of both systems, the distinct operating time scale between various logistics and energy equipment and the uncertainties stemming from both systems. To this end, a multi-stage stochastic integer program (MSSIP) formulation of seaport coordinated logistics–energy scheduling problem is proposed, accounting for non-negligible operating time scale of different equipment. It features holistic modeling of the container handling and logistics process at both quay and yard sides, while jointly optimizing the energy management strategy of the energy system, in face of multiple uncertainties arising from ship arrival times, cargo demand and renewable energy generation. To accurately reflect the propagation of multi-source uncertainties across time and take into account their impact on the sequential scheduling decisions, a Markov chain stochastic dual dynamic integer programming algorithm is developed for efficient decomposed solution of MSSIP, while promising favorable optimality and convergence properties. Dynamic conditional value-at-risk is integrated into the model for dynamic risk management. Case studies carried out based on real-world data and settings of Ningbo Zhoushan port revealed significant techno-economic benefits associated with coordinated energy and logistics scheduling for (i) port operators, achieving a total of 27.81 % reduction in total logistics and energy costs and (ii) power grid, achieving 18.25 % mitigation of concentrated demand peaks and 100 % improvement in RES absorption, with respect to separated and sub-optimal scheduling. Sensitivity analysis under varying arrivals and workloads shows that heavier workloads increase rescheduling pressure and costly electricity use, highlighting the need for greater flexibility. Risk management insights are also provided for port operators in face of dynamic multi-source uncertainties.