Developing a Simulation Framework for Optimizing CO2-Capture Processes

DEVELOPING A SIMULATION FRAMEWORK

FOR OPTIMIZING CO₂-CAPTURE PROCESSES

Stuart Higgins and Y. A. Liu

PetroChina-AspenTech Center of Excellence in Process System Engineering,

Department of Chemical Engineering, Virginia Polytechnic Institute and State University,

Blacksburg, VA 24061

We have reported¹ a highly efficient, amine-based CO₂-capture unit design, achieving a thermal regeneration energy of merely 1.67 GJ/(tonne CO₂ captured).  While our results look promising, the optimization of our process superstructure required a significant amount of effort, largely due to the number of optimization parameters and our use of computationally expensive rigorous models.

 

This experience motivated us to develop a more practical simulation framework.  We focus on a modular design that allows us to use commercial modeling tools, and develop an overall simulation structure to take advantage of multi-threading, distribution, custom convergence methods, error recovery, and other features for increasing productivity.

Our new software framework enables faster, more reliable, more productive process optimization, while still using the same rigorous modeling tools validated by respected vendors.  Multi-threading allows us to take advantage of the increasing core counts on modern CPUs, while distribution is similarly important as computational devices become more numerous.

In this talk, we will discuss the simulation framework and its application to optimize generalized process designs.  We expect these improvements to enable optimizations that would otherwise require far too much time and effort to complete.  We are particularly interested in superstructure process designs that generalize base-case process designs with potential improvements, because we can optimize these superstructures to find new process designs.

                             

¹ Stuart J. Higgins and Y. A. Liu, “CO₂ Capture Modeling, Energy Savings, and Heat Pump Integration”, Industrial and Engineering Chemistry Research, 54, 2526-2553 (2015).