Technoeconomic analysis reveals that solar-powered metal hydride storage reduces imported grid electricity by 67% in an office building, highlighting the feasibility of hydrogen systems.
The present study examines the dynamic energy, environmental, and economic performance of a power-to- H 2 -to-power production and storage system based on metal-hydride (MH) technology, integrated as a hybrid energy storage solution for a renovated office building in Ptolemaida, Greece. The system utilizes nominal 10 kW p rooftop photovoltaics (PV), with a containerized unit comprising a 7 kW e proton exchange membrane (PEM) electrolyzer, a 3 kg hydrogen storage MH tank, and a 10 kW e PEM fuel cell. Eight alternative operational scenarios are examined for various PV capacities and MH storage sizes based on a parametric energy analysis. Annual dynamic energy simulations are performed using the INTEMA tool, a dynamic high-fidelity house-built process model applicable in building and energy systems, while the environmental and economic evaluation is conducted through the house-built life-cycle assessment/life-cycle costing tool, VERIFY, interoperable with INTEMA one, over a 50-year period. The findings illustrate that upsizing PV capacity increases energy autonomy, providing improvements of up to 40% compared to the baseline case, while MH storage size exhibits marginal benefits beyond the critical range of 4 to 5 kg. A multicriteria assessment has been utilized to optimize energy autonomy from the grid, life-cycle costs, and global warming potential. Under equal weighting of all criteria, the scenario with 120 kW p PV capacity and a 4 kg MH tank emerges as the optimal configuration, achieving the highest energy self-sufficiency by reducing imported grid electricity to approximately 67% and whole life cost by 24% compared to the baseline case, while maintaining a balanced environmental performance. The findings highlight the techno-economic viability of hydrogen-based storage systems in building-scale applications and provide practical insights for optimal system sizing under multiple sustainability objectives.
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Ziozas et al. (2026) studied this question.
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