A rigorous computationally effcient
closed-loop system with a gain-scheduled
model predictive controller (MPC) is developed for the first time,
where a first-principle model of the steam methane reformer is utilized
to represent the process dynamics. A dynamic model for a generic primary
gas reformer is developed using a homogeneous-phase one-dimensional
reaction kinetics model to describe the chemical reactions inside
the reforming tubes and to compute the external heat transfer to the
reformer tubes by radiation and convection. The gain-scheduled MPC
considers critical process parameters of the steam methane reformer
such as outlet methane molar concentration and outlet temperature
of the reformed gas as the most appropriate and reliable process variables.
The developed gain-scheduled MPC demonstrates adaptive and advanced
operation of the steam methane reformer at three different steam-to-carbon
ratios. By simulation of the set-point changes under the influence
of the steam methane reformer critical disturbance rejection performances,
it is shown that reformer tubes could operate in a safe temperature
range. The model determines optimal trajectories of the reformed syngas
outlet temperature and methane outlet molar concentration based on
tracking the set point under the influence of the manipulated variablestemperature
and mass rate of mixed feed and fuel flow rate for burners. The gain-scheduled
MPC is compared with already proven standard process control solutions
based on proportional-integral-derivative (PID) controllers. Proposed
control strategy benefits include energy savings in the range from
3% to 5% and prolonged lifetime of the reformer tubes and catalyst.
Reforming of natural gas with steam represents the most energy-intensive part of ammonia production. An integrated numerical model for calculating composition of primary reforming products with cross-checking of outlet methane molar concentration, heat duty, maximum tube wall temperature, tube pressure drops, and approach to equilibrium was set up involving production parameters. In particular, the model was used for continuous monitoring and optimization of a steam methane reformer (SMR) catalyst in ammonia production. The calculations involve the solution of material and energy balance equations along with reaction kinetic expressions. Open source code based on Matlab file was used for modelling and calculation of various physical properties of the reacting gases. One of the main contributions is development of the rapid integrated method for data exchange between any distributed control system (DCS) and the model to accomplish continuous monitoring and optimization of SMR catalyst and reformer tubes. Integrated memory block was proposed for rapid synchronization between commercial DCS with the model solver. The developed model was verified with the industrial top-fired SMR unit in ammonia production located in Petrokemija, Croatia. Practical application of proposed solution can ensure overall energy savings of up to 3% in ammonia production.
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