Abstract
Hydrogen-fueled vehicles are a promising technology for reducing CO2 emissions in the mobility sector. This paper presents a stochastic receding horizon controller for operating a real-world hydrogen refueling station in a cost-efficient manner, while considering uncertainty in the hydrogen demand. We derive grey-box models for the system and we use them to formulate a predictive control taking the form of a mixed-integer linear program. We solve it by relying on the scenario approach and we ensure a reduced computational footprint by resorting on a non-uniform prediction horizon discretization and on a Lagrangian-based decomposition method.
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