Demand-Driven Techno-Economic Optimization of an Integrated Green Hydrogen Energy System with Pipeline Transport Using Particle Swarm Optimization: A Hospital Case Study in Ouarzazate, Morocco

The decarbonization of hospitals located in remote regions with water stress requires a power source that is both reliable and cost-effective. The use of a green hydrogen energy system is proposed for use as the power source for the medical sector located in Ouarzazate, Morocco. The system utilizes photovoltaic panels to power proton exchange membrane (PEM) electrolyzers, which generate hydrogen fuel that is stored in a pipeline to the hospital site where it can be utilized in a fuel cell. A model was created in MATLAB/Simulink R2023a that considered the backward-propagation algorithm to size each of the components of the hydrogen energy system, which was optimized using the particle swarm optimization algorithm. The sizing results of the model indicated that a 924 kW electrolyzer, a 217 kW fuel cell, a 21.5 kW compressor, a 30 mm diameter pipeline, and a 7400 m2 area for the photovoltaic panels are required to supply 161 kg of hydrogen per day to the hospital. The hydrogen fuel system will meet the demand of the hospital for 159 kg of hydrogen per day with a zero loss of load at the deterministic design point, in both the representative day and five-day cloudy-period stress test horizons; a full-physics Monte Carlo uncertainty analysis (N = 10,000 draws) further shows that this reliability outcome is not robust to combined ±20% uncertainty in electrolyzer efficiency and component unit costs, with zero loss of load maintained in 62.8% of draws. The installation cost of the hydrogen fuel system is approximately 8.21 M EUR. Furthermore, because the hydrogen fuel is stored upstream from the hospital, the flow rate of hydrogen fuel that passes through the pipeline is less than if it were stored downstream from the hospital. Finally, the levelized cost of hydrogen fuel of the system is approximately 13.67 EUR/kg, which shows limited sensitivity to the considered variations in solar irradiance. Thus, this hydrogen fuel system methodology can be applied to other types of critical loads, especially those critical loads within hospitals, in regions with high solar potential.