Bi-level distributionally robust coordinated optimization of integrateed energy system and hydrogen refueling station based on stackelberg game

The coordinated operation of integrated energy system (IES) and hydrogen refueling station (HRS) is crucial for advancing the hydrogen vehicle industry and achieving dual carbon goals. However, competition between their interests, along with uncertainties in renewable energy generation and hydrogen demand, significantly compromises system economics, stability, and hydrogen storage safety. Traditional scheduling models inadequately address the thermal and electrical demands of carbon capture system (CCS) and struggle to balance robustness in handling uncertainty with computational efficiency, thereby limiting their engineering applicability. This study proposes a bi-level distributionally robust coordination mechanism based on stackelberg game theory, developing a refined model for the coordinated operation of combined heat and power (CHP), CCS, and power-to-gas (P2G) technologies. An equivalent reformulation strategy is designed to transition from two-stage distributionally robust optimization (TSDRO) to two-stage robust optimization (TSRO), incorporating distributionally robust chance constraint (DRCC) for the safe capacity of hydrogen storage tank. The proposed sequential bound tightening nested improved constraint & column generation (SBT-nested-IC&CG) algorithm, offers efficient computational solutions. Simulation results indicate that the method effectively balances the interests of both parties, enhances robustness against multiple uncertainties, maintains reasonable hydrogen storage safety levels, and reduces computation time by approximately 50 % compared to traditional nested column & constraint generation (NC&CG) algorithm, thus providing a feasible engineering solution for the coordinated scheduling of IES and HRS