Addressing Spatiotemporal Mismatch via Hourly Pipeline Scheduling: Regional Hydrogen Energy Supply Optimization

Abstract

The rapid adoption of hydrogen fuel cell vehicles (HFCVs) in the Beijing–Tianjin–Hebei (BTH) hub accentuates the mismatch between renewable-based hydrogen supply in Hebei and concentrated demand in Beijing and Tianjin. We develop a mixed-integer linear model that co-configures a hydrogen pipeline network and optimizes hourly flow schedules to minimize annualized cost and CO2 emissions simultaneously. For 15,000 HFCVs expected in 2025 (137 t d−1 demand), the Pareto-optimal design consists of 13 production plants, 43 pipelines and 38 refueling stations, delivering 50 767 t yr−1 at 68% pipeline utilization. Hebei provides 88% of the hydrogen, 70% of which is consumed in the two megacities. Hourly profiles reveal that 65% of electrolytic output coincides with local wind–solar peaks, whereas refueling surges arise during morning and evening rush hours; the proposed schedule offsets the 4–6 h mismatch without additional storage. Transport distances are 40% < 50 km, 35% 50–200 km, and 25% > 200 km. Raising the green hydrogen share from 10% to 70% increases total system cost from USD 1.56 bn to USD 2.73 bn but cuts annual CO2 emissions from 142 kt to 51 kt, demonstrating the trade-off between cost and decarbonization. The model quantifies the value of sub-day pipeline scheduling in resolving spatial–temporal imbalances for large-scale low-carbon hydrogen supply.