(384e) Dynamic Simulation and Optimization for Gas Expanded Liquid Phase of Ethylene Oxide Production with Free Carbon Dioxide Emission | AIChE

(384e) Dynamic Simulation and Optimization for Gas Expanded Liquid Phase of Ethylene Oxide Production with Free Carbon Dioxide Emission


Abou Shama, M. A. - Presenter, Lamar University
Xu, Q., Lamar University
Ethylene oxide production is considered as one of the processes that produce carbon dioxide as byproduct. In response to the global warming issue, the following work illustrates alternative synthesis to produce ethylene oxide with free carbon dioxide emission. The new procedure was found by The Center for Environmentally Beneficial Catalysis (CEBC), University of Kansan and improved by Laboratory of Integrated Systems Engineering (LISE), Lamar University. The ethylene oxide is produced by reacting ethylene and hydrogen peroxide which is the reaction oxidant over methyltrioxorhenium catalyst (MTO) in a continuous stirred reactor at 104 áµ’F and 725.18 psia.

At LISE, the new steady state design has been built on Aspen Plus version 8.8, focusing on solving some of the problems that have been mentioned by CEBE and improving the distillation and purification process. Therefore, the design is consisted of two continuous stirred reactors, a flash drum, a trays column, and two packed bed columns. In response to the waste of unreacted hydrogen peroxide, a better design layout set has been developed to recycle and regenerate that hydrogen peroxide back to the main epoxidation reactor. Fortunately, these adjustments lead to optimize the alternative ethylene oxide synthesis, it decreases the production cost to 52 ¢/lb. of ethylene oxide, and the payback period for new ethylene oxide production plant is 3.48 year which is evaluated by Aspen Process Economic Analyzer.

For further studies on the process safety and process operation stability, a dynamic well controlled model is built in Aspen Dynamic version 8.8. The safety of the process has been assigned as the first priority, and the process capability is the second priority in designing the control scheme and control parameters tuning for the dynamic model. First, the conversion in the main epoxidation reactor is controlled by the reactor temperature to specified value, so the catalyst stays as active as possible. Second, with the hydrogen peroxide decomposer, the decomposition reaction is controlled by the reactor temperature to ensure that all the hydrogen peroxide is decomposed before entering the separation and purification step. As well as, the reactor vapor outlet composition is controlled by the reactor pressure to keep that out of the flammability zone for ethylene oxide, ethylene, and methanol (which is reaction solvent). Third, with the hydrogen peroxide recycle stream, the decomposed oxygen is regenerated to hydrogen peroxide; therefore, the main control objective is to make sure all oxygen is converted to hydrogen peroxide before they reenter the epoxidation reactor. Fourth, with the distillation columns, the main objective for the first tower is to recycle most of the unreacted ethylene back to the epoxidation reactor. On the second column, the objective is to get the water in the bottom stream to be pure as much as 99.995% mol. On the last column, the objective is to achieve the desired market purity for ethylene oxide. Finally, by applying all the previous objectives and specifications to the model, the process operation stability could respond on any disturbance that is generated by upstream set point changes up to 15% of its steady state values.

Also, we have gone further, and we rebuilt the control system in the DeltaV DCS system to control the simulated process through OPC Client server, so we can have a more realistic and reliable model to the real plant operation. Right now, we are working on alarm rationalization study using DeltaV system, and it will be done by the conference time. Beside that work, we will make a model predictive control model which will be generated by Aspen DMC Plus and DeltaV that will be used to do further study on dynamic optimization and real time optimization.