Multi-segment flexibility-based optimization scheduling for integrated energy systems coupled with electric and hydrogen fuel cell vehicles

Flexible resources are crucial for mitigating the impacts of variability and uncertainty in integrated energy systems. However, existing approaches predominantly focus on isolated segments such as storage or load, without considering their combined and coordinated effects, which leads to suboptimal system-level performance. This paper proposes a unified operational optimization framework that integrates multi-source flexibility, including storage systems, demand-side response, vehicle-to-grid services from electric vehicles and hydrogen vehicles, and virtual flexibility from energy networks. A probabilistic modeling approach is employed to explicitly characterize the behavioral dynamics of EVs and HVs, including state-of-charge evolution, arrival/departure schedules, and their coupling with hydrogen production. A system-level indicator set is designed to evaluate the marginal contributions of different flexibility resources in terms of cost reduction, ramping capability, and supply-demand stability. The proposed framework is compatible with IoT-based sensing and edge-computing platforms to enable real-time implementation. Case results show that integrating flexibility reduces supply-demand deviation by 4.47 % and operational costs by 17.71 %. EV and HV flexibility, hydrogen storage, and virtual energy network storage improve cost-effectiveness. Hydrogen storage reduces costs by up to 6400 CNY, while virtual storage saves 83.00 CNY/day with no operational costs. Under variable V2G pricing, energy procurement costs drop to 3600 CNY. Flexibility contributions from each segment are quantified, with the most significant cost reduction from load-side flexibility (10.09 %) followed by storage flexibility. Sensitivity analysis shows that system performance improves and stabilizes with increased equipment capacity. This study underscores the critical role of multi-segment flexibility coordination in achieving cost-effective, adaptive, and robust operation of future distributed energy systems.