Decarbonizing the transportation sector requires quick adoption of low-carbon energy carriers, with green hydrogen becoming a promising option for zero/low-emission mobility. Hydrogen refueling stations powered by renewable energy sources present a practical way to cut down lifecycle greenhouse gases and ease grid congestion. Nonetheless, most existing photovoltaic (PV)-based hydrogen production systems focus solely on electrical aspects, overlooking thermal energy flows and temperature effects that greatly impact PV and Electrolyzer performance. This study provides a thorough techno-economic evaluation of a hybrid PV/photovoltaic-thermal (PVT) green hydrogen system for refueling stations. The simulation framework models the combined electrical, thermal, and hydrogen subsystems under realistic conditions, incorporating rooftop PV/PVT collectors, battery storage, a water Electrolyzer, and hydrogen storage. Thermal energy from the PVT is used to pre-heat Electrolyzer feedwater, lowering electricity demand for hydrogen production and boosting PV efficiency via active cooling. Hydrogen production follows a demand-driven control strategy based on randomly generated stochastic daily refueling events. Three configurations are compared: (i) grid-only electrolysis, (ii) PV-only assisted electrolysis, and (iii) fully integrated PV/PVT-assisted electrolysis. The results show that the integrated PV/PVT setup significantly increases self-consumption, autarky rate, and overall efficiency, while lowering reliance on grid electricity and hydrogen production costs. Developed case studies highlight the economic feasibility and real-world viability of PV/PVT-assisted (decentralized) hydrogen refueling infrastructure.

With the rapid global expansion of renewable energy installations, green hydrogen has gained growing interest as a flexible energy carrier capable of supporting sector coupling, seasonal storage, and industrial decarbonization. Renewable Energy Communities (RECs) represent a promising organizational structure for decentralized green hydrogen production; however, the integration of multiple interconnected RECs through local hydrogen transport networks remains insufficiently characterized. This study presents a Mixed-Integer Linear Programming (MILP) framework for the techno-economic optimization of interconnected REC-based hydrogen networks. The framework combines renewable electricity generation with battery storage, local hydrogen production and storage, pipeline and truck transport, and a conceptual central hydrogen hub for exports. Representative-day clustering is used to reduce computational complexity while preserving annual operational characteristics. The model determines optimal hydrogen flows, pipeline investments, truck dispatch when pipelines are not economically viable, and hub exports under predefined economic and environmental constraints. A case study comprising four interconnected RECs representative of Central European conditions is investigated. The optimization relocates the central hub to the largest exporter. Three of the five identified pipeline corridors are economically justified under the baseline assumptions, with the built pipelines transporting 99.3% of the total hydrogen moved within the network, while truck transport accounts for 0.7%. The central hub exports aggregated surplus hydrogen, generating annual revenues above EUR 460,000. No unmet hydrogen demand remains after optimization. The results show that interconnected green-hydrogen REC networks can improve renewable-energy utilization, reduce curtailment, enhance regional energy resilience, and create hydrogen business opportunities, while also indicating that the economic conclusions are sensitive to infrastructure cost, utilization, and price assumptions.