(662e) Identification of a Reduced Order Data-Driven Model of a Hydrogen Production Plant

Hydrogen is one of the most important chemical components widely used in petroleum and chemical industries. An economic way to commercially produce hydrogen is to utilize steam methane reforming [1]. The process consists of a number of material and heat flows, resulting in an intricate network of material and energy. Natural gas (NG) and superheated steam are fed to a chemical reactor called reformer, which consists of catalyst tubes filled with nickel reforming catalyst. Here, majority of the hydrogen is produced. The gas out of the reformer is then processed through another reactor to further produce hydrogen. Finally, the hydrogen flow is purified in a pressure swing adsorber (PSA), where high purity hydrogen is produced. The reformer exit temperature is an important process variable for this process and is expected to be kept at a desired level by heating the reformer. This heat is provided by burning the off-gas from the PSA and NG fuel stream. A fan is used to supply air to the burners and another one draws the combustion products, termed as flue gas, out of the reformer box.

This process presents various constraints and challenges during the start-up as well as nominal operation of the plant such as, the reformer exit temperature should be maintained at a desirable level. Further, the firebox pressure should not breach its lower and upper limits for safety. If the pressure is too low, the fire can be extinguished. If it is too high, it may impose safety hazards to facility and personnel [2].

In this work, we design a safe and optimal start-up strategy for the unit as it goes from the shutdown conditions to the nominal operating phase. A desired characteristic is to optimize the process in such a way that it minimizes the start-up time and the cost while achieving the desired specifications of the hydrogen produced. To this end, first a high fidelity model of the entire plant is developed to be used as a test bed. Then a data driven model [3-4] utilizing simulation data from the high fidelity model is developed for the purpose of optimizing the startup. Simulation results are presented that illustrate the improvement achieved by implementation of the optimization based startup.

[1] JL Lynn and BH Bory. Kirk-othmer encyclopedia of chemical technology, 2000.

[2] Miao Du, Prashant Mhaskar, Yu Zhu, and Jesus Flores-Cerrillo (2014). Safe-Parking of a Hydrogen Production Unit. Industrial & Engineering Chemistry Research, 53 (19), 8147-8154.

[3] S. Aumi, B. Corbett, P. Mhaskar, and T. Clarke-Pringle. Data-based modeling and control of nylon-6, 6 batch polymerization. Control Systems Technology, IEEE Transactions on, 21(1):94-106, Jan 2013.

[4] Aumi, S. and P. Mhaskar. An Adaptive Data-based Modeling Approach for Predictive Control of Batch Systems. Chem. Eng. Sci., 21, 94-106, 2013.