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.

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.

This paper examines the potential of utilizing photovoltaic (PV) systems on noise barriers along Austrian railway lines and their possible integration into Renewable Energy Communities. In line with Austria’s climate goals to cover the entire electricity consumption from renewable sources by 2030, the study analyzes how existing infrastructures, particularly noise barriers, can be used for solar power generation without the need for additional land. The future expansion of noise barriers, projected to increase by 135 km by 2030, is also considered. Data from the Austrian Federal Railways (ÖBB) and simulations are used to forecast power yields under various geographic and technical conditions. Factors such as the orientation of noise barriers, shading effects, and module efficiency are incorporated into the calculations. The PVGIS simulation tool is utilized to account for regional variations and their impact on solar energy production. Furthermore, the study investigates how the generated energy could be integrated into existing Renewable Energy Communities to support decentralized and community-based energy supply. A case study of a Renewable Energy Community illustrates how such a concept can be implemented. The analysis also includes a scenario-based approach, evaluating potential electricity generation across different technological development pathways. Depending on the progress of PV technologies and the expansion speed of noise barriers, annual electricity production could range from 50 to 90 GWh. Limiting factors such as physical efficiency constraints and geographical limitations are also analyzed. The study emphasizes the importance of flexible solutions, such as energy storage and optimized grid integration. The results provide a foundation for assessing the potential of PV systems on noise barriers along Austrian railway lines, as well as their integration into existing infrastructures and Renewable Energy Communities, contributing to decentralized energy supply and climate targets.