Robust scheduling of a port power system with shore-power load uncertainty, dynamic shore-power pricing, and hybrid hydrogen–battery storage

Shore-power demand in ports is highly dependent on vessel arrivals, departures, berthing duration, and vessel-type differences. These operating features make conventional aggregated load models insufficient for coordinated scheduling. This paper proposes a two-stage robust scheduling model for a port distribution network–multi-microgrid system considering vessel-behavior-driven shore-power load uncertainty, dynamic shore-power pricing, and hybrid hydrogen–battery storage. By combining vessel-type classification, vessel-level parameterization, arrival/departure perturbations, and microgrid-level aggregation, a shore-power load model and its uncertainty representation are developed to capture the overlapping berthing effect of multiple vessels and the time-varying uncertainty of shore-power demand. Dynamic shore-power pricing is used to better reflect practical port operation, while a hybrid hydrogen–battery storage system is incorporated to leverage the complementary characteristics of fast-responding batteries and long-duration hydrogen storage, effectively smoothing multi-timescale power fluctuations, facilitating efficient wind power accommodation, and enhancing the intertemporal regulation flexibility and economic efficiency of the port microgrid. The proposed model is solved through a hierarchical ATC–C&CG framework, which coordinates the distribution network and microgrids and optimizes recourse decisions under worst-case scenarios. Case studies show that the total social cost is 20,632.50 CNY, the served shore-power energy reaches 7078.64 kWh, and no load shedding or renewable energy curtailment occurs. Comparative results indicate that the proposed uncertainty model can describe practical port operation disturbances, dynamic shore-power pricing improves shore-power revenue without reducing the service level, and hybrid hydrogen–battery storage enhances microgrid intertemporal regulation flexibility under wind power fluctuations.