This paper proposes a Mixed Logical Dynamical (MLD) model for a real-world Hydrogen Refuelling Station (HRS) currently under development, incorporating on-site production, multi-pressure hydrogen storage, and discrete event-triggered refuelling processes. By modelling the HRS using the expanded linear state-space MLD formulation with linear inequality constraints, the model accommodates hydrogen flows, pressure thresholds, and discontinuous behaviour within this unified framework suitable for automatic control/decision-making purposes. To illustrate the usefulness of the proposed modelling approach, a preliminary Hybrid Model Predictive Control (HMPC) scheme and a Constraint Satisfaction Problem (CSP) formulation are proposed, leveraging the MLD structure for optimization-based control and feasibility validation in the face of unpredicted Fuel-Cell Electric Vehicle (FCEV) arrivals. The case of study simulation results highlight how the MLD model addresses the logical and event-triggered behaviours and constraints commonly neglected by aggregated models reported in scheduling-based approaches present in the gross body of literature concerning HRS operation. The implemented HMPC strategy and the CSP statement primarily demonstrate the model’s practical utility. These approaches also hint at their potential for developing advanced operational strategies—ranging from stochastic or multi-level control schemes to distributed architectures—and for deeper sizing analyses or performance assessments of real-world HRSs. Consequently, the proposed modelling approach provides a robust foundation for innovation in hydrogen infrastructure management, bridging essential gaps in the literature by integrating discrete logic decisions, multi-tank refuelling topologies, and online optimization under real operating constraints.