Scenario-driven day-ahead–intraday coordination of seaport virtual power plants under heterogeneous load uncertainty

Abstract

Seaport virtual power plants (SVPPs) face strong load uncertainty caused by ship berthing, crane operation, and electric heavy-duty truck battery swapping demand. To improve scheduling robustness, this paper proposes a scenario-driven day-ahead–intraday coordination method for SVPPs. Monte Carlo simulation is used to generate ship shore power and battery swapping station load scenarios, and crane load is modeled as an operation-related derived load. Wind–photovoltaic output is then incorporated to construct port-area net load scenarios. Based on net load peak, ramp rate, and duration, the rated power and capacity of energy storage are determined. A day-ahead dispatch model and an intraday rolling correction model are further developed to coordinate electricity purchase, energy storage operation, renewable energy accommodation, and power shortage mitigation. Case studies show that energy storage reduces the total operating cost by 9.79% and the maximum electricity purchase deviation by 52.11%, while the proposed coordination method reduces the execution-stage cost by 18.4%. The results verify the effectiveness of the proposed method under port load uncertainty.