Multimodel Simulations of Hydrogen Refueling Stations: Stock Levels, Infrastructure, and Performance Evaluation Under Stochastic Vehicle Inflows in the Gulf–Europe Corridor

This study employs multimodel simulations, including road traffic, process, and system dynamics modeling, to analyze hydrogen refueling stations (HRSs) in the Gulf–Europe corridor, also known as the Iraq’s development road project (DRP). It focuses on operational requirements, which consist of stock levels and infrastructure needs, along with refueling performance under stochastic vehicle inflows (SVIs) from the Gulf, European countries, and Iraq’s side roads (SRs). The research aims to identify key operational requirements and evaluate the refueling performance of an HRS for various stochastic vehicle inflow (SVI) scenarios, facilitating the efficient integration of hydrogen fuel cell vehicles (HFCVs) into freight networks. The study introduces novel multimodel simulations developed in the AnyLogic software environment to replicate real-world variability in vehicle inflows. Key findings reveal that SVIs significantly impact hydrogen stock level (HSL), infrastructure requirements (IRs), and refueling performance metrics (RPMs). For example, for a daily transportation demand of 30,000 tons of goods with 10%–20% side road (SR) vehicle entries, an HRS requires an IR-1 of 3, an IR-2 of 2, and an HSL of 44,391.6 kg, with performance reflected in refueling performance metric (RPM)-1 values of 73%, 72%, and 45%, and an RPM-2 range of 1.32–6.12 min. This proves that the HRS requirements and performance vary with SVIs for different transportation demands. Hence, we enhance the theoretical framework of refueling station design by integrating multimodel simulations to address stochastic inflows. It offers actionable insights for policymakers on optimizing HRS operations, improving scalability, and achieving United Nations sustainable development goals (SDGs).