(547c) Enterprise-Wide Modular Process Intensification and Multi-Scale Optimization for Natural Gas Utilization | AIChE

(547c) Enterprise-Wide Modular Process Intensification and Multi-Scale Optimization for Natural Gas Utilization

Authors 

Iyer, S. S. - Presenter, Texas A&M University
Demirel, S. E., The Dow Chemical Company
Hasan, F., Texas A&M University
Natural gas will account for about 25% of the total energy consumption from primary sources by 2035.1 It is also a clean fossil fuel source with abundant reserves. Though methane (CH4) is the main component of natural gas, some of the natural gas reserves are uneconomical for exploitation due to high CO2 contents sometimes up to 70% by volume.2 CO2 contents are also high for unconventional sources of methane such as biogas, coal bed methane, land fill gas etc. To meet specifications for transport through pipelines, the level of impurities in methane has to be less than 3–4 %. Existing standalone technologies for separation of methane from impurities involve separation, compression for pipeline transport and storage for consumption by the end user. The separation step usually via pressure swing adsorption (PSA) involves high pressure for sufficient adsorption, followed by vacuum depressurization for regeneration of the adsorbent, followed by re-pressurization for pipeline transportation. The successive pressure changes and the lack of integration between these steps makes the supply chain energy and capital intensive. Moreover, small and stranded sources of methane are not economical for pipeline transportation.

We have developed a modular one-step process3 which intensifies the separation and storage of methane from sources in the same unit thereby eliminating the pressure changes involved in the supply chain. The technology is based on preferential adsorption of CH4 using micro-porous materials such as zeolites. In this combined separation and storage (CSS) process, a mixture of CH4/CO2/CH4 is fed to the column filled with zeolite, where CH4 get separated and is stored in the column till the column is saturated while impurities leave the column from the other end. The column/modular unit saturated with CH4 can then be used in applications such as vehicles and be sent back after use for refilling. The CSS process is described by a non-linear algebraic partial differential equation (NAPDE) model which incorporates mass and energy conservation equations, pressure drop correlations, driving force for mass transfer into the adsorbent and the adsorbent isotherm relating the equilibrium gas loading on the adsorbent material. To obtain optimal operating conditions for the process, the model is completely discretized in space and time into a system of non-linear algebraic equations whose size increases with the level of discretization.

To screen the existing zeolite materials along with process optimization, binary variables relating to the isotherm parameters are introduced into the model. We have also performed Grand Canonical Monte Carlo (GCMC) simulations for CH4, CO2 and N2 on pure silica zeolites in the IZA-SC database to obtain the adsorption loading data at different pressures and temperatures. The isotherm model parameters are then obtained by solving the minimization problem of least-square error between the data and predicted model to global optimality. The simultaneous process optimization and materials screening problem thus becomes a mixed integer non-linear programming (MINLP) problem. We have solved the model to optimality to simultaneously select the best zeolite and the best design of the CSS process. Results indicate that the storage capacity of CH4 on the material must be balanced with the requisite purity of the stored CH4 by identifying the best material along with the corresponding optimal conditions, as the storage capacity and selectivity may not both be high enough for a given material. The multi-scale optimization framework developed herein is not only applied for simultaneous process optimization and materials screening but is also used to predict the values of optimal hypothetical isotherm parameters for the current application. This can assist experimental efforts to design best materials for gas separation and storage applications.

 

References:

(1) BP. Energy Outlook 2017; British Petroleum, 2017.

(2) First, E. L.; Hasan, M. M. F.; Floudas, C. A. Discovery of Novel Zeolites for Natural Gas Purification through Combined Material Screening and Process Optimization. AIChE J. 2014, 60 (5), 1767–1785.

(3) Iyer, S. S.; Hasan, M. M. F. A Novel Plug-and-Store Technology for Natural Gas Purification and Strage. In CAMX 2015 - Composites and Advanced Materials Expo; 2015.