Multi-Time-Scale Low-Carbon optimal scheduling for Electric-Hydrogen integrated energy systems incorporating flexible Vehicle-to-Grid technology

• Leveraging hydrogen energy for long-term storage and carbon reduction. • Constructed a coordinated four-stage scheduling model with multi-temporal scales. • Incorporated flexible vehicle-to-grid modes for electric and hydrogen vehicles. • High renewable energy penetration enhances the value of hydrogen and vehicle-to-grid systems. The hydrogen-permeated integrated energy system possesses the characteristic of long-cycle energy balance, making traditional three-stage scheduling frameworks, comprising day-ahead, intraday, and real-time stages, insufficient to meet the demand for flexible operation over long time scales. To address this challenge, this study proposes a four-stage, multi-time-scale low-carbon optimal scheduling method for an electric-hydrogen integrated energy system that incorporates flexible vehicle-to-grid (V2G) technology. This method encompasses coordinated scheduling at the weekly, day-ahead, intraday, and real-time levels to achieve global resource optimization. First, a multi-energy complementary system architecture with the deep coupling of electricity, heat, gas, and hydrogen is constructed, and the stochastic driving behaviors of electric vehicles and hydrogen fuel cell vehicles are modeled using Monte Carlo simulations. Furthermore, flexible V2G models applicable to both vehicle types are embedded into the scheduling strategy to enhance operational flexibility effectively. On this basis, a carbon trading mechanism is introduced to establish a multi-time-scale low-carbon economic dispatch model that minimizes the system’s total operational cost. Simulation results demonstrate that the introduction of flexible V2G technology reduces the cost of curtailed photovoltaic energy by approximately 3.11%. Compared to traditional integrated energy system scheduling models, the proposed model reduces the total system cost by nearly 17.83%. Furthermore, under the proposed multi-time-scale scheduling strategy, both the photovoltaic utilization rate and the system’s energy self-sufficiency rate are significantly improved. In conclusion, the proposed scheduling strategy demonstrates substantial potential to enhance the system’s economic efficiency, low-carbon performance, and operational flexibility.