Development of a high fidelity and subspace identification model of a hydrogen plant startup dynamics

In this work, the problem of determining a data-driven model of a hydrogen production unit is addressed. The framework is applied to a high fidelity simulation model developed in this work. To this end, first a high fidelity model of the entire plant is developed in Honeywell's UniSim Design, capable of simulating the startup and shutdown phase, with appropriate adaptation of the plant standard operating procedure (SOP). Several startups are simulated to generate training data for identification of a data-driven model. Then an LTI data-driven model of the process using subspace identification based methods is determined and validated against new simulated startup. Simulation results demonstrate the prediction capabilities of the identified model.