Capacity Optimization of Renewable-Based Hydrogen Production–Refueling Station for Fuel Cell Electric Vehicles: A Real-Project-Based Case Study

With the deepening electrification of transportation, hydrogen fuel cell electric vehicles (FCEVs) are emerging as a vital component of clean and electrified transportation systems. Nonetheless, renewable-based hydrogen production–refueling stations (HPRSs) for FCEVs still need solid models for accurate simulations and a practical capacity optimization method for cost reduction. To address this gap, this study leverages real operation data from China’s largest HPRS to establish and validate a comprehensive model integrating hydrogen production, storage, renewables, FCEVs, and the power grid. Building on this validated model, a novel capacity optimization framework is proposed, incorporating an improved Jellyfish Search Algorithm (JSA) to minimize the initial investment cost, operating cost, and levelized cost of hydrogen (LCOH). The results demonstrate the framework’s significant innovations and effectiveness: It achieves the maximum reductions of 29.31% in the initial investment, 100% in the annual operational cost, and 44.19% in LCOH while meeting FCEV demand. Simultaneously, it reduces peak grid load by up to 43.80% and enables renewable energy to cover up to 89.30% of transportation hydrogen demand. This study contributes to enhancing economic performance and optimizing the design and planning of HPRS for FCEVs, as well as promoting sustainable transportation electrification.