New process development and process evaluation for capturing CO2 in flue gas from power plants using ionic liquid[emim][Tf2N]

Using the ionic liquid[emim][Tf2N]as a physical solvent,it was found by Aspen Plus simulation that it was possible to attempt to capture CO2 from the flue gas discharged from the coal-fired unit of the power plant.Using the combination of model calculation and experimental determination,the density,isostatic heat capacity,viscosity,vapor pressure,thermal conductivity,surface tension and solubility of[emim][Tf2N]were obtained.Based on the NRTL model,the Henry coefficient and NRTL binary interaction parameters of CO2 dissolved in[emim][Tf2N]were obtained by correlating[emim][Tf2N]with the gas–liquid equilibrium data of CO2.Firstly,the calculated relevant data is imported into Aspen Plus,and the whole process model of the ionic liquid absorption process is established.Then the absorption process is optimized according to the temperature distribution in the absorption tower to obtain a new absorption process.Finally,the density,constant pressure heat capacity,surface tension,thermal conductivity,and viscosity of[emim][Tf2N]were changed to investigate the effect of ionic liquid properties on process energy consumption,solvent circulation and heat exchanger design.The results showed that based on the composition of the inlet gas stream to the absorbers,CO2 with a capture rate of 90%and a mass purity higher than 99.5%was captured.These results indicate that the[emim][Tf2N]could be used as a physical solvent for CO2 capture from coal-fired units.In addition,the results will provide a theoretical basis for the design of new ionic liquids for CO2 capture.

Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure

In this paper,a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-loop reference trajectory and the actual process.In the upper layer,the variant time scale based control vector parametric methods(VTS-CVP) was used for dynamic optimization of transition reference trajectory,while nonlinear model predictive controller(NMPC) based on closed-loop subspace and piece-wise linear(SSARX-PWL) model in the lower layer was tracking to the reference trajectory from the upper layer for overcoming high-frequency disturbances.Besides,mechanism about trajectory deviation detection and optimal trajectory updating online were introduced to ensure a smooth transition for the entire process.The proposed method was validated with the real data from an industrial double-loop propylene polymerization reaction process with developed dynamic mechanism mathematical model.

Modeling and Multi-objective Optimization of Refinery Hydrogen Network

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.